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Code Issues Actions 16 Packages Projects Releases Wiki Activity

build: rename main → llama-cli, server → llama-server, llava-cli → llama-llava-cli, etc... (#7809)

Browse Source 
* `main`/`server`: rename to `llama` / `llama-server` for consistency w/ homebrew

* server: update refs -> llama-server

gitignore llama-server

* server: simplify nix package

* main: update refs -> llama

fix examples/main ref

* main/server: fix targets

* update more names

* Update build.yml

* rm accidentally checked in bins

* update straggling refs

* Update .gitignore

* Update server-llm.sh

* main: target name -> llama-cli

* Prefix all example bins w/ llama-

* fix main refs

* rename {main->llama}-cmake-pkg binary

* prefix more cmake targets w/ llama-

* add/fix gbnf-validator subfolder to cmake

* sort cmake example subdirs

* rm bin files

* fix llama-lookup-* Makefile rules

* gitignore /llama-*

* rename Dockerfiles

* rename llama|main -> llama-cli; consistent RPM bin prefixes

* fix some missing -cli suffixes

* rename dockerfile w/ llama-cli

* rename(make): llama-baby-llama

* update dockerfile refs

* more llama-cli(.exe)

* fix test-eval-callback

* rename: llama-cli-cmake-pkg(.exe)

* address gbnf-validator unused fread warning (switched to C++ / ifstream)

* add two missing llama- prefixes

* Updating docs for eval-callback binary to use new `llama-` prefix.

* Updating a few lingering doc references for rename of main to llama-cli

* Updating `run-with-preset.py` to use new binary names.
Updating docs around `perplexity` binary rename.

* Updating documentation references for lookup-merge and export-lora

* Updating two small `main` references missed earlier in the finetune docs.

* Update apps.nix

* update grammar/README.md w/ new llama-* names

* update llama-rpc-server bin name + doc

* Revert "update llama-rpc-server bin name + doc"

This reverts commit e474ef1df4.

* add hot topic notice to README.md

* Update README.md

* Update README.md

* rename gguf-split & quantize bins refs in **/tests.sh

---------

Co-authored-by: HanClinto <hanclinto@gmail.com>
This commit is contained in:
Olivier Chafik 2024-06-13 00:41:52 +01:00 committed by GitHub
parent 963552903f
commit 1c641e6aac
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
128 changed files with 578 additions and 578 deletions
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2
.devops/cloud-v-pipeline
View File

@ -15,7 +15,7 @@ node('x86_runner1'){ // Running on x86 runner containing latest vecto
stage('Running llama.cpp'){
sh'''#!/bin/bash
module load gnu-bin2/0.1 # loading latest versions of vector qemu and vector gcc
qemu-riscv64 -L /softwares/gnu-bin2/sysroot -cpu rv64,v=true,vlen=256,elen=64,vext_spec=v1.0 ./main -m /home/alitariq/codellama-7b.Q4_K_M.gguf -p "Anything" -n 9 > llama_log.txt # Running llama.cpp on vector qemu-riscv64
qemu-riscv64 -L /softwares/gnu-bin2/sysroot -cpu rv64,v=true,vlen=256,elen=64,vext_spec=v1.0 ./llama-cli -m /home/alitariq/codellama-7b.Q4_K_M.gguf -p "Anything" -n 9 > llama_log.txt # Running llama.cpp on vector qemu-riscv64
cat llama_log.txt # Printing results
'''
}

6
.devops/main-cuda.Dockerfile → .devops/llama-cli-cuda.Dockerfile
View File

@ -23,13 +23,13 @@ ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
# Enable CUDA
ENV LLAMA_CUDA=1
RUN make -j$(nproc) main
RUN make -j$(nproc) llama-cli
FROM ${BASE_CUDA_RUN_CONTAINER} as runtime
RUN apt-get update && \
apt-get install -y libgomp1
COPY --from=build /app/main /main
COPY --from=build /app/llama-cli /llama-cli
ENTRYPOINT [ "/main" ]
ENTRYPOINT [ "/llama-cli" ]

6
.devops/main-intel.Dockerfile → .devops/llama-cli-intel.Dockerfile
View File

@ -15,12 +15,12 @@ RUN if [ "${LLAMA_SYCL_F16}" = "ON" ]; then \
export OPT_SYCL_F16="-DLLAMA_SYCL_F16=ON"; \
fi && \
cmake -B build -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx ${OPT_SYCL_F16} && \
cmake --build build --config Release --target main
cmake --build build --config Release --target llama-cli
FROM intel/oneapi-basekit:$ONEAPI_VERSION as runtime
COPY --from=build /app/build/bin/main /main
COPY --from=build /app/build/bin/llama-cli /llama-cli
ENV LC_ALL=C.utf8
ENTRYPOINT [ "/main" ]
ENTRYPOINT [ "/llama-cli" ]

4
.devops/main-rocm.Dockerfile → .devops/llama-cli-rocm.Dockerfile
View File

@ -40,6 +40,6 @@ ENV LLAMA_HIPBLAS=1
ENV CC=/opt/rocm/llvm/bin/clang
ENV CXX=/opt/rocm/llvm/bin/clang++
RUN make -j$(nproc) main
RUN make -j$(nproc) llama-cli
ENTRYPOINT [ "/app/main" ]
ENTRYPOINT [ "/app/llama-cli" ]

6
.devops/main-vulkan.Dockerfile → .devops/llama-cli-vulkan.Dockerfile
View File

@ -15,13 +15,13 @@ RUN wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key
WORKDIR /app
COPY . .
RUN cmake -B build -DLLAMA_VULKAN=1 && \
cmake --build build --config Release --target main
cmake --build build --config Release --target llama-cli
# Clean up
WORKDIR /
RUN cp /app/build/bin/main /main && \
RUN cp /app/build/bin/llama-cli /llama-cli && \
rm -rf /app
ENV LC_ALL=C.utf8
ENTRYPOINT [ "/main" ]
ENTRYPOINT [ "/llama-cli" ]

6
.devops/main.Dockerfile → .devops/llama-cli.Dockerfile
View File

@ -9,15 +9,15 @@ WORKDIR /app
COPY . .
RUN make -j$(nproc) main
RUN make -j$(nproc) llama-cli
FROM ubuntu:$UBUNTU_VERSION as runtime
RUN apt-get update && \
apt-get install -y libgomp1
COPY --from=build /app/main /main
COPY --from=build /app/llama-cli /llama-cli
ENV LC_ALL=C.utf8
ENTRYPOINT [ "/main" ]
ENTRYPOINT [ "/llama-cli" ]

14
.devops/llama-cpp-clblast.srpm.spec
View File

@ -36,9 +36,9 @@ make -j LLAMA_CLBLAST=1
%install
mkdir -p %{buildroot}%{_bindir}/
cp -p main %{buildroot}%{_bindir}/llamaclblast
cp -p server %{buildroot}%{_bindir}/llamaclblastserver
cp -p simple %{buildroot}%{_bindir}/llamaclblastsimple
cp -p llama-cli %{buildroot}%{_bindir}/llama-clblast-cli
cp -p llama-server %{buildroot}%{_bindir}/llama-clblast-server
cp -p llama-simple %{buildroot}%{_bindir}/llama-clblast-simple
mkdir -p %{buildroot}/usr/lib/systemd/system
%{__cat} <<EOF > %{buildroot}/usr/lib/systemd/system/llamaclblast.service
@ -49,7 +49,7 @@ After=syslog.target network.target local-fs.target remote-fs.target nss-lookup.t
[Service]
Type=simple
EnvironmentFile=/etc/sysconfig/llama
ExecStart=/usr/bin/llamaclblastserver $LLAMA_ARGS
ExecStart=/usr/bin/llama-clblast-server $LLAMA_ARGS
ExecReload=/bin/kill -s HUP $MAINPID
Restart=never
@ -67,9 +67,9 @@ rm -rf %{buildroot}
rm -rf %{_builddir}/*
%files
%{_bindir}/llamaclblast
%{_bindir}/llamaclblastserver
%{_bindir}/llamaclblastsimple
%{_bindir}/llama-clblast-cli
%{_bindir}/llama-clblast-server
%{_bindir}/llama-clblast-simple
/usr/lib/systemd/system/llamaclblast.service
%config /etc/sysconfig/llama

14
.devops/llama-cpp-cuda.srpm.spec
View File

@ -36,9 +36,9 @@ make -j LLAMA_CUDA=1
%install
mkdir -p %{buildroot}%{_bindir}/
cp -p main %{buildroot}%{_bindir}/llamacppcuda
cp -p server %{buildroot}%{_bindir}/llamacppcudaserver
cp -p simple %{buildroot}%{_bindir}/llamacppcudasimple
cp -p llama-cli %{buildroot}%{_bindir}/llama-cuda-cli
cp -p llama-server %{buildroot}%{_bindir}/llama-cuda-server
cp -p llama-simple %{buildroot}%{_bindir}/llama-cuda-simple
mkdir -p %{buildroot}/usr/lib/systemd/system
%{__cat} <<EOF > %{buildroot}/usr/lib/systemd/system/llamacuda.service
@ -49,7 +49,7 @@ After=syslog.target network.target local-fs.target remote-fs.target nss-lookup.t
[Service]
Type=simple
EnvironmentFile=/etc/sysconfig/llama
ExecStart=/usr/bin/llamacppcudaserver $LLAMA_ARGS
ExecStart=/usr/bin/llama-cuda-server $LLAMA_ARGS
ExecReload=/bin/kill -s HUP $MAINPID
Restart=never
@ -67,9 +67,9 @@ rm -rf %{buildroot}
rm -rf %{_builddir}/*
%files
%{_bindir}/llamacppcuda
%{_bindir}/llamacppcudaserver
%{_bindir}/llamacppcudasimple
%{_bindir}/llama-cuda-cli
%{_bindir}/llama-cuda-server
%{_bindir}/llama-cuda-simple
/usr/lib/systemd/system/llamacuda.service
%config /etc/sysconfig/llama

14
.devops/llama-cpp.srpm.spec
View File

@ -38,9 +38,9 @@ make -j
%install
mkdir -p %{buildroot}%{_bindir}/
cp -p main %{buildroot}%{_bindir}/llama
cp -p server %{buildroot}%{_bindir}/llamaserver
cp -p simple %{buildroot}%{_bindir}/llamasimple
cp -p llama-cli %{buildroot}%{_bindir}/llama-cli
cp -p llama-server %{buildroot}%{_bindir}/llama-server
cp -p llama-simple %{buildroot}%{_bindir}/llama-simple
mkdir -p %{buildroot}/usr/lib/systemd/system
%{__cat} <<EOF > %{buildroot}/usr/lib/systemd/system/llama.service
@ -51,7 +51,7 @@ After=syslog.target network.target local-fs.target remote-fs.target nss-lookup.t
[Service]
Type=simple
EnvironmentFile=/etc/sysconfig/llama
ExecStart=/usr/bin/llamaserver $LLAMA_ARGS
ExecStart=/usr/bin/llama-server $LLAMA_ARGS
ExecReload=/bin/kill -s HUP $MAINPID
Restart=never
@ -69,9 +69,9 @@ rm -rf %{buildroot}
rm -rf %{_builddir}/*
%files
%{_bindir}/llama
%{_bindir}/llamaserver
%{_bindir}/llamasimple
%{_bindir}/llama-cli
%{_bindir}/llama-server
%{_bindir}/llama-simple
/usr/lib/systemd/system/llama.service
%config /etc/sysconfig/llama

6
.devops/server-cuda.Dockerfile → .devops/llama-server-cuda.Dockerfile
View File

@ -25,13 +25,13 @@ ENV LLAMA_CUDA=1
# Enable cURL
ENV LLAMA_CURL=1
RUN make -j$(nproc) server
RUN make -j$(nproc) llama-server
FROM ${BASE_CUDA_RUN_CONTAINER} as runtime
RUN apt-get update && \
apt-get install -y libcurl4-openssl-dev libgomp1
COPY --from=build /app/server /server
COPY --from=build /app/llama-server /llama-server
ENTRYPOINT [ "/server" ]
ENTRYPOINT [ "/llama-server" ]

6
.devops/server-intel.Dockerfile → .devops/llama-server-intel.Dockerfile
View File

@ -15,15 +15,15 @@ RUN if [ "${LLAMA_SYCL_F16}" = "ON" ]; then \
export OPT_SYCL_F16="-DLLAMA_SYCL_F16=ON"; \
fi && \
cmake -B build -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_CURL=ON ${OPT_SYCL_F16} && \
cmake --build build --config Release --target server
cmake --build build --config Release --target llama-server
FROM intel/oneapi-basekit:$ONEAPI_VERSION as runtime
RUN apt-get update && \
apt-get install -y libcurl4-openssl-dev
COPY --from=build /app/build/bin/server /server
COPY --from=build /app/build/bin/llama-server /llama-server
ENV LC_ALL=C.utf8
ENTRYPOINT [ "/server" ]
ENTRYPOINT [ "/llama-server" ]

4
.devops/server-rocm.Dockerfile → .devops/llama-server-rocm.Dockerfile
View File

@ -45,6 +45,6 @@ ENV LLAMA_CURL=1
RUN apt-get update && \
apt-get install -y libcurl4-openssl-dev
RUN make -j$(nproc)
RUN make -j$(nproc) llama-server
ENTRYPOINT [ "/app/server" ]
ENTRYPOINT [ "/app/llama-server" ]

6
.devops/server-vulkan.Dockerfile → .devops/llama-server-vulkan.Dockerfile
View File

@ -19,13 +19,13 @@ RUN apt-get update && \
WORKDIR /app
COPY . .
RUN cmake -B build -DLLAMA_VULKAN=1 -DLLAMA_CURL=1 && \
cmake --build build --config Release --target server
cmake --build build --config Release --target llama-server
# Clean up
WORKDIR /
RUN cp /app/build/bin/server /server && \
RUN cp /app/build/bin/llama-server /llama-server && \
rm -rf /app
ENV LC_ALL=C.utf8
ENTRYPOINT [ "/server" ]
ENTRYPOINT [ "/llama-server" ]

6
.devops/server.Dockerfile → .devops/llama-server.Dockerfile
View File

@ -11,15 +11,15 @@ COPY . .
ENV LLAMA_CURL=1
RUN make -j$(nproc) server
RUN make -j$(nproc) llama-server
FROM ubuntu:$UBUNTU_VERSION as runtime
RUN apt-get update && \
apt-get install -y libcurl4-openssl-dev libgomp1
COPY --from=build /app/server /server
COPY --from=build /app/llama-server /llama-server
ENV LC_ALL=C.utf8
ENTRYPOINT [ "/server" ]
ENTRYPOINT [ "/llama-server" ]

6
.devops/nix/apps.nix
View File

@ -6,11 +6,11 @@
let
inherit (config.packages) default;
binaries = [
"llama"
"llama-cli"
"llama-embedding"
"llama-server"
"quantize"
"train-text-from-scratch"
"llama-quantize"
"llama-train-text-from-scratch"
];
mkApp = name: {
type = "app";

4
.devops/nix/package.nix
View File

@ -243,8 +243,6 @@ effectiveStdenv.mkDerivation (
# TODO(SomeoneSerge): It's better to add proper install targets at the CMake level,
# if they haven't been added yet.
postInstall = ''
mv $out/bin/main${executableSuffix} $out/bin/llama${executableSuffix}
mv $out/bin/server${executableSuffix} $out/bin/llama-server${executableSuffix}
mkdir -p $out/include
cp $src/llama.h $out/include/
'';
@ -294,7 +292,7 @@ effectiveStdenv.mkDerivation (
license = lib.licenses.mit;
# Accommodates `nix run` and `lib.getExe`
mainProgram = "llama";
mainProgram = "llama-cli";
# These people might respond, on the best effort basis, if you ping them
# in case of Nix-specific regressions or for reviewing Nix-specific PRs.

10
.devops/tools.sh
View File

@ -10,11 +10,11 @@ shift
if [[ "$arg1" == '--convert' || "$arg1" == '-c' ]]; then
python3 ./convert-hf-to-gguf.py "$@"
elif [[ "$arg1" == '--quantize' || "$arg1" == '-q' ]]; then
./quantize "$@"
./llama-quantize "$@"
elif [[ "$arg1" == '--run' || "$arg1" == '-r' ]]; then
./main "$@"
./llama-cli "$@"
elif [[ "$arg1" == '--finetune' || "$arg1" == '-f' ]]; then
./finetune "$@"
./llama-finetune "$@"
elif [[ "$arg1" == '--all-in-one' || "$arg1" == '-a' ]]; then
echo "Converting PTH to GGML..."
for i in `ls $1/$2/ggml-model-f16.bin*`; do
@ -22,11 +22,11 @@ elif [[ "$arg1" == '--all-in-one' || "$arg1" == '-a' ]]; then
echo "Skip model quantization, it already exists: ${i/f16/q4_0}"
else
echo "Converting PTH to GGML: $i into ${i/f16/q4_0}..."
./quantize "$i" "${i/f16/q4_0}" q4_0
./llama-quantize "$i" "${i/f16/q4_0}" q4_0
fi
done
elif [[ "$arg1" == '--server' || "$arg1" == '-s' ]]; then
./server "$@"
./llama-server "$@"
else
echo "Unknown command: $arg1"
echo "Available commands: "

4
.dockerignore
View File

@ -12,8 +12,8 @@ build*/
models/*
/main
/quantize
/llama-cli
/llama-quantize
arm_neon.h
compile_commands.json

2
.github/ISSUE_TEMPLATE/01-bug-low.yml vendored
View File

@ -24,7 +24,7 @@ body:
label: Name and Version
description: Which executable and which version of our software are you running? (use `--version` to get a version string)
placeholder: |
$./main --version
$./llama-cli --version
version: 2999 (42b4109e)
built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
validations:

2
.github/ISSUE_TEMPLATE/02-bug-medium.yml vendored
View File

@ -24,7 +24,7 @@ body:
label: Name and Version
description: Which executable and which version of our software are you running? (use `--version` to get a version string)
placeholder: |
$./main --version
$./llama-cli --version
version: 2999 (42b4109e)
built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
validations:

2
.github/ISSUE_TEMPLATE/03-bug-high.yml vendored
View File

@ -24,7 +24,7 @@ body:
label: Name and Version
description: Which executable and which version of our software are you running? (use `--version` to get a version string)
placeholder: |
$./main --version
$./llama-cli --version
version: 2999 (42b4109e)
built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
validations:

2
.github/ISSUE_TEMPLATE/04-bug-critical.yml vendored
View File

@ -24,7 +24,7 @@ body:
label: Name and Version
description: Which executable and which version of our software are you running? (use `--version` to get a version string)
placeholder: |
$./main --version
$./llama-cli --version
version: 2999 (42b4109e)
built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
validations:

2
.github/workflows/bench.yml vendored
View File

@ -119,7 +119,7 @@ jobs:
-DLLAMA_FATAL_WARNINGS=OFF \
-DLLAMA_ALL_WARNINGS=OFF \
-DCMAKE_BUILD_TYPE=Release;
cmake --build build --config Release -j $(nproc) --target server
cmake --build build --config Release -j $(nproc) --target llama-server
- name: Download the dataset
id: download_dataset

10
.github/workflows/build.yml vendored
View File

@ -103,12 +103,10 @@ jobs:
id: cmake_build
run: |
sysctl -a
mkdir build
cd build
# Metal is disabled due to intermittent failures with Github runners not having a GPU:
# https://github.com/ggerganov/llama.cpp/actions/runs/8635935781/job/23674807267#step:5:2313
cmake -DLLAMA_FATAL_WARNINGS=ON -DLLAMA_METAL=OFF -DLLAMA_CURL=ON ..
cmake --build . --config Release -j $(sysctl -n hw.logicalcpu)
cmake -B build -DLLAMA_FATAL_WARNINGS=ON -DLLAMA_METAL=OFF -DLLAMA_CURL=ON
cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
- name: Test
id: cmake_test
@ -241,8 +239,8 @@ jobs:
wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/tok512.bin
echo "Fetch llama2c model"
wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories260K/stories260K.bin
./bin/convert-llama2c-to-ggml --copy-vocab-from-model ./tok512.bin --llama2c-model stories260K.bin --llama2c-output-model stories260K.gguf
./bin/main -m stories260K.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
./bin/llama-convert-llama2c-to-ggml --copy-vocab-from-model ./tok512.bin --llama2c-model stories260K.bin --llama2c-output-model stories260K.gguf
./bin/llama-cli -m stories260K.gguf -p "One day, Lily met a Shoggoth" -n 500 -c 256
- name: Determine tag name
id: tag

16
.github/workflows/docker.yml vendored
View File

@ -30,20 +30,20 @@ jobs:
strategy:
matrix:
config:
- { tag: "light", dockerfile: ".devops/main.Dockerfile", platforms: "linux/amd64,linux/arm64" }
- { tag: "light", dockerfile: ".devops/llama-cli.Dockerfile", platforms: "linux/amd64,linux/arm64" }
- { tag: "server", dockerfile: ".devops/llama-server.Dockerfile", platforms: "linux/amd64,linux/arm64" }
- { tag: "full", dockerfile: ".devops/full.Dockerfile", platforms: "linux/amd64,linux/arm64" }
- { tag: "server", dockerfile: ".devops/server.Dockerfile", platforms: "linux/amd64,linux/arm64" }
# NOTE(canardletter): The CUDA builds on arm64 are very slow, so I
# have disabled them for now until the reason why
# is understood.
- { tag: "light-cuda", dockerfile: ".devops/main-cuda.Dockerfile", platforms: "linux/amd64" }
- { tag: "light-cuda", dockerfile: ".devops/llama-cli-cuda.Dockerfile", platforms: "linux/amd64" }
- { tag: "server-cuda", dockerfile: ".devops/llama-server-cuda.Dockerfile", platforms: "linux/amd64" }
- { tag: "full-cuda", dockerfile: ".devops/full-cuda.Dockerfile", platforms: "linux/amd64" }
- { tag: "server-cuda", dockerfile: ".devops/server-cuda.Dockerfile", platforms: "linux/amd64" }
- { tag: "light-rocm", dockerfile: ".devops/main-rocm.Dockerfile", platforms: "linux/amd64,linux/arm64" }
- { tag: "light-rocm", dockerfile: ".devops/llama-cli-rocm.Dockerfile", platforms: "linux/amd64,linux/arm64" }
- { tag: "server-rocm", dockerfile: ".devops/llama-server-rocm.Dockerfile", platforms: "linux/amd64,linux/arm64" }
- { tag: "full-rocm", dockerfile: ".devops/full-rocm.Dockerfile", platforms: "linux/amd64,linux/arm64" }
- { tag: "server-rocm", dockerfile: ".devops/server-rocm.Dockerfile", platforms: "linux/amd64,linux/arm64" }
- { tag: "light-intel", dockerfile: ".devops/main-intel.Dockerfile", platforms: "linux/amd64" }
- { tag: "server-intel", dockerfile: ".devops/server-intel.Dockerfile", platforms: "linux/amd64" }
- { tag: "light-intel", dockerfile: ".devops/llama-cli-intel.Dockerfile", platforms: "linux/amd64" }
- { tag: "server-intel", dockerfile: ".devops/llama-server-intel.Dockerfile", platforms: "linux/amd64" }
steps:
- name: Check out the repo
uses: actions/checkout@v4

4
.github/workflows/server.yml vendored
View File

@ -96,7 +96,7 @@ jobs:
-DLLAMA_CURL=ON \
-DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
-DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON ;
cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target server
cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
- name: Tests
id: server_integration_tests
@ -136,7 +136,7 @@ jobs:
id: cmake_build
run: |
cmake -B build -DLLAMA_CURL=ON -DCURL_LIBRARY="$env:RUNNER_TEMP/libcurl/lib/libcurl.dll.a" -DCURL_INCLUDE_DIR="$env:RUNNER_TEMP/libcurl/include"
cmake --build build --config Release -j ${env:NUMBER_OF_PROCESSORS} --target server
cmake --build build --config Release -j ${env:NUMBER_OF_PROCESSORS} --target llama-server
- name: Python setup
id: setup_python

43
.gitignore vendored
View File

@ -46,48 +46,9 @@ models/*
models-mnt
/Pipfile
/baby-llama
/beam-search
/benchmark-matmult
/convert-llama2c-to-ggml
/embd-input-test
/embedding
/eval-callback
/gguf
/gguf-llama-simple
/gguf-split
/gritlm
/imatrix
/infill
/libllama.so
/llama-bench
/llava-cli
/lookahead
/lookup
/lookup-create
/lookup-merge
/lookup-stats
/main
/metal
/passkey
/perplexity
/q8dot
/quantize
/quantize-stats
/result
/save-load-state
/server
/simple
/batched
/batched-bench
/export-lora
/finetune
/retrieval
/speculative
/parallel
/train-text-from-scratch
/tokenize
/vdot
/llama-*
llama-batched-swift
/common/build-info.cpp
arm_neon.h
compile_commands.json

138
Makefile
View File

@ -1,8 +1,44 @@
# Define the default target now so that it is always the first target
BUILD_TARGETS = \
main quantize quantize-stats perplexity imatrix embedding vdot q8dot train-text-from-scratch convert-llama2c-to-ggml \
simple batched batched-bench save-load-state server gguf gguf-split eval-callback llama-bench libllava.a llava-cli baby-llama \
retrieval speculative infill tokenize benchmark-matmult parallel finetune export-lora lookahead lookup passkey gritlm tests/test-c.o
libllava.a \
llama-baby-llama \
llama-batched \
llama-batched-bench \
llama-bench \
llama-benchmark-matmult \
llama-cli \
llama-convert-llama2c-to-ggml \
llama-embedding \
llama-eval-callback \
llama-export-lora \
llama-finetune \
llama-gbnf-validator \
llama-gguf \
llama-gguf-split \
llama-gritlm \
llama-imatrix \
llama-infill \
llama-llava-cli \
llama-lookahead \
llama-lookup \
llama-lookup-create \
llama-lookup-merge \
llama-lookup-stats \
llama-parallel \
llama-passkey \
llama-perplexity \
llama-q8dot \
llama-quantize \
llama-quantize-stats \
llama-retrieval \
llama-save-load-state \
llama-server \
llama-simple \
llama-speculative \
llama-tokenize \
llama-train-text-from-scratch \
llama-vdot \
tests/test-c.o
# Binaries only useful for tests
TEST_TARGETS = \
@ -777,7 +813,7 @@ libllama.a: llama.o ggml.o $(OBJS) $(COMMON_DEPS)
ar rcs libllama.a llama.o ggml.o $(OBJS) $(COMMON_DEPS)
clean:
rm -vrf *.o tests/*.o *.so *.a *.dll benchmark-matmult lookup-create lookup-merge lookup-stats common/build-info.cpp *.dot $(COV_TARGETS) $(BUILD_TARGETS) $(TEST_TARGETS)
rm -vrf *.o tests/*.o *.so *.a *.dll common/build-info.cpp *.dot $(COV_TARGETS) $(BUILD_TARGETS) $(TEST_TARGETS)
rm -vrf ggml-cuda/*.o
rm -vrf ggml-cuda/template-instances/*.o
find examples pocs -type f -name "*.o" -delete
@ -793,62 +829,62 @@ clean:
# Helper function that replaces .c, .cpp, and .cu file endings with .o:
GET_OBJ_FILE = $(patsubst %.c,%.o,$(patsubst %.cpp,%.o,$(patsubst %.cu,%.o,$(1))))
main: examples/main/main.cpp ggml.o llama.o $(COMMON_DEPS) console.o grammar-parser.o $(OBJS)
llama-cli: examples/main/main.cpp ggml.o llama.o $(COMMON_DEPS) console.o grammar-parser.o $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
@echo
@echo '==== Run ./main -h for help. ===='
@echo '==== Run ./llama-cli -h for help. ===='
@echo
infill: examples/infill/infill.cpp ggml.o llama.o $(COMMON_DEPS) console.o grammar-parser.o $(OBJS)
llama-infill: examples/infill/infill.cpp ggml.o llama.o $(COMMON_DEPS) console.o grammar-parser.o $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
simple: examples/simple/simple.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
llama-simple: examples/simple/simple.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
tokenize: examples/tokenize/tokenize.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
llama-tokenize: examples/tokenize/tokenize.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
batched: examples/batched/batched.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
llama-batched: examples/batched/batched.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
batched-bench: examples/batched-bench/batched-bench.cpp build-info.o ggml.o llama.o $(COMMON_DEPS) $(OBJS)
llama-batched-bench: examples/batched-bench/batched-bench.cpp build-info.o ggml.o llama.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
quantize: examples/quantize/quantize.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
llama-quantize: examples/quantize/quantize.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
quantize-stats: examples/quantize-stats/quantize-stats.cpp build-info.o ggml.o llama.o $(OBJS)
llama-quantize-stats: examples/quantize-stats/quantize-stats.cpp build-info.o ggml.o llama.o $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
perplexity: examples/perplexity/perplexity.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
llama-perplexity: examples/perplexity/perplexity.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
imatrix: examples/imatrix/imatrix.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
llama-imatrix: examples/imatrix/imatrix.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
embedding: examples/embedding/embedding.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
llama-embedding: examples/embedding/embedding.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
gritlm: examples/gritlm/gritlm.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
llama-gritlm: examples/gritlm/gritlm.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
save-load-state: examples/save-load-state/save-load-state.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
llama-save-load-state: examples/save-load-state/save-load-state.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
server: examples/server/server.cpp examples/server/utils.hpp examples/server/httplib.h common/json.hpp examples/server/colorthemes.css.hpp examples/server/style.css.hpp examples/server/theme-beeninorder.css.hpp examples/server/theme-ketivah.css.hpp examples/server/theme-mangotango.css.hpp examples/server/theme-playground.css.hpp examples/server/theme-polarnight.css.hpp examples/server/theme-snowstorm.css.hpp examples/server/index.html.hpp examples/server/index-new.html.hpp examples/server/index.js.hpp examples/server/completion.js.hpp examples/server/system-prompts.js.hpp examples/server/prompt-formats.js.hpp examples/server/json-schema-to-grammar.mjs.hpp common/stb_image.h ggml.o llama.o $(COMMON_DEPS) grammar-parser.o $(OBJS)
llama-server: examples/server/server.cpp examples/server/utils.hpp examples/server/httplib.h common/json.hpp examples/server/colorthemes.css.hpp examples/server/style.css.hpp examples/server/theme-beeninorder.css.hpp examples/server/theme-ketivah.css.hpp examples/server/theme-mangotango.css.hpp examples/server/theme-playground.css.hpp examples/server/theme-polarnight.css.hpp examples/server/theme-snowstorm.css.hpp examples/server/index.html.hpp examples/server/index-new.html.hpp examples/server/index.js.hpp examples/server/completion.js.hpp examples/server/system-prompts.js.hpp examples/server/prompt-formats.js.hpp examples/server/json-schema-to-grammar.mjs.hpp common/stb_image.h ggml.o llama.o $(COMMON_DEPS) grammar-parser.o $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h %.hpp $<,$^) -Iexamples/server $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS) $(LWINSOCK2)
@ -861,23 +897,23 @@ examples/server/%.hpp: examples/server/public/% Makefile
echo "unsigned int $${NAME}_len = $(shell cat $< | wc -c );" \
) > $@
gguf: examples/gguf/gguf.cpp ggml.o $(OBJS)
llama-gguf: examples/gguf/gguf.cpp ggml.o $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
gguf-split: examples/gguf-split/gguf-split.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
llama-gguf-split: examples/gguf-split/gguf-split.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
eval-callback: examples/eval-callback/eval-callback.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
llama-eval-callback: examples/eval-callback/eval-callback.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
train-text-from-scratch: examples/train-text-from-scratch/train-text-from-scratch.cpp ggml.o llama.o $(COMMON_DEPS) train.o $(OBJS)
llama-train-text-from-scratch: examples/train-text-from-scratch/train-text-from-scratch.cpp ggml.o llama.o $(COMMON_DEPS) train.o $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
convert-llama2c-to-ggml: examples/convert-llama2c-to-ggml/convert-llama2c-to-ggml.cpp ggml.o llama.o $(OBJS)
llama-convert-llama2c-to-ggml: examples/convert-llama2c-to-ggml/convert-llama2c-to-ggml.cpp ggml.o llama.o $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
@ -888,55 +924,61 @@ llama-bench: examples/llama-bench/llama-bench.cpp ggml.o llama.o $(COMMON_DEPS)
libllava.a: examples/llava/llava.cpp examples/llava/llava.h examples/llava/clip.cpp examples/llava/clip.h common/stb_image.h common/base64.hpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -static -fPIC -c $< -o $@ -Wno-cast-qual
llava-cli: examples/llava/llava-cli.cpp examples/llava/clip.h examples/llava/clip.cpp examples/llava/llava.h examples/llava/llava.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
llama-llava-cli: examples/llava/llava-cli.cpp examples/llava/clip.h examples/llava/clip.cpp examples/llava/llava.h examples/llava/llava.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) -c examples/llava/clip.cpp -o $(call GET_OBJ_FILE, examples/llava/clip.cpp) -Wno-cast-qual
$(CXX) $(CXXFLAGS) -c examples/llava/llava.cpp -o $(call GET_OBJ_FILE, examples/llava/llava.cpp)
$(CXX) $(CXXFLAGS) $(filter-out %.h $< examples/llava/clip.cpp examples/llava/llava.cpp,$^) $(call GET_OBJ_FILE, $<) $(call GET_OBJ_FILE, examples/llava/clip.cpp) $(call GET_OBJ_FILE, examples/llava/llava.cpp) -o $@ $(LDFLAGS)
baby-llama: examples/baby-llama/baby-llama.cpp ggml.o llama.o $(COMMON_DEPS) train.o $(OBJS)
llama-baby-llama: examples/baby-llama/baby-llama.cpp ggml.o llama.o $(COMMON_DEPS) train.o $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
finetune: examples/finetune/finetune.cpp ggml.o llama.o $(COMMON_DEPS) train.o $(OBJS)
llama-finetune: examples/finetune/finetune.cpp ggml.o llama.o $(COMMON_DEPS) train.o $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
export-lora: examples/export-lora/export-lora.cpp ggml.o common/common.h $(OBJS)
llama-export-lora: examples/export-lora/export-lora.cpp ggml.o common/common.h $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
retrieval: examples/retrieval/retrieval.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
llama-retrieval: examples/retrieval/retrieval.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
speculative: examples/speculative/speculative.cpp ggml.o llama.o $(COMMON_DEPS) grammar-parser.o $(OBJS)
llama-speculative: examples/speculative/speculative.cpp ggml.o llama.o $(COMMON_DEPS) grammar-parser.o $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
parallel: examples/parallel/parallel.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
llama-parallel: examples/parallel/parallel.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
lookahead: examples/lookahead/lookahead.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
llama-lookahead: examples/lookahead/lookahead.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
lookup: examples/lookup/lookup.cpp ggml.o llama.o ngram-cache.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
$(CXX) $(CXXFLAGS) -c examples/lookup/lookup-create.cpp -o $(call GET_OBJ_FILE, examples/lookup/lookup-create.cpp)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, examples/lookup/lookup-create.cpp) -o lookup-create $(LDFLAGS)
$(CXX) $(CXXFLAGS) -c examples/lookup/lookup-merge.cpp -o $(call GET_OBJ_FILE, examples/lookup/lookup-merge.cpp)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, examples/lookup/lookup-merge.cpp) -o lookup-merge $(LDFLAGS)
$(CXX) $(CXXFLAGS) -c examples/lookup/lookup-stats.cpp -o $(call GET_OBJ_FILE, examples/lookup/lookup-stats.cpp)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, examples/lookup/lookup-stats.cpp) -o lookup-stats $(LDFLAGS)
passkey: examples/passkey/passkey.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
llama-lookup: examples/lookup/lookup.cpp ggml.o llama.o ngram-cache.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
gbnf-validator: examples/gbnf-validator/gbnf-validator.cpp ggml.o llama.o $(COMMON_DEPS) grammar-parser.o $(OBJS)
llama-lookup-create: examples/lookup/lookup-create.cpp ggml.o llama.o ngram-cache.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
llama-lookup-merge: examples/lookup/lookup-merge.cpp ggml.o llama.o ngram-cache.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
llama-lookup-stats: examples/lookup/lookup-stats.cpp ggml.o llama.o ngram-cache.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
llama-passkey: examples/passkey/passkey.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
llama-gbnf-validator: examples/gbnf-validator/gbnf-validator.cpp ggml.o llama.o $(COMMON_DEPS) grammar-parser.o $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
@ -962,20 +1004,20 @@ build-info.o: common/build-info.cpp
tests: $(TEST_TARGETS)
benchmark-matmult: examples/benchmark/benchmark-matmult.cpp build-info.o ggml.o $(OBJS)
llama-benchmark-matmult: examples/benchmark/benchmark-matmult.cpp build-info.o ggml.o $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out %.h $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
run-benchmark-matmult: benchmark-matmult
run-benchmark-matmult: llama-benchmark-matmult
./$@
.PHONY: run-benchmark-matmult swift
vdot: pocs/vdot/vdot.cpp ggml.o $(OBJS)
llama-vdot: pocs/vdot/vdot.cpp ggml.o $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)
q8dot: pocs/vdot/q8dot.cpp ggml.o $(OBJS)
llama-q8dot: pocs/vdot/q8dot.cpp ggml.o $(OBJS)
$(CXX) $(CXXFLAGS) -c $< -o $(call GET_OBJ_FILE, $<)
$(CXX) $(CXXFLAGS) $(filter-out $<,$^) $(call GET_OBJ_FILE, $<) -o $@ $(LDFLAGS)

18
README-sycl.md
View File

@ -77,7 +77,7 @@ It has the similar design of other llama.cpp BLAS-based paths such as *OpenBLAS,
*Notes:*
- **Memory**
- The device memory is a limitation when running a large model. The loaded model size, *`llm_load_tensors: buffer_size`*, is displayed in the log when running `./bin/main`.
- The device memory is a limitation when running a large model. The loaded model size, *`llm_load_tensors: buffer_size`*, is displayed in the log when running `./bin/llama-cli`.
- Please make sure the GPU shared memory from the host is large enough to account for the model's size. For e.g. the *llama-2-7b.Q4_0* requires at least 8.0GB for integrated GPU and 4.0GB for discrete GPU.
@ -99,14 +99,14 @@ The docker build option is currently limited to *intel GPU* targets.
### Build image
```sh
# Using FP16
docker build -t llama-cpp-sycl --build-arg="LLAMA_SYCL_F16=ON" -f .devops/main-intel.Dockerfile .
docker build -t llama-cpp-sycl --build-arg="LLAMA_SYCL_F16=ON" -f .devops/llama-cli-intel.Dockerfile .
```
*Notes*:
To build in default FP32 *(Slower than FP16 alternative)*, you can remove the `--build-arg="LLAMA_SYCL_F16=ON"` argument from the previous command.
You can also use the `.devops/server-intel.Dockerfile`, which builds the *"server"* alternative.
You can also use the `.devops/llama-server-intel.Dockerfile`, which builds the *"server"* alternative.
### Run container
@ -275,7 +275,7 @@ source /opt/intel/oneapi/setvars.sh
Similar to the native `sycl-ls`, available SYCL devices can be queried as follow:
```sh
./build/bin/ls-sycl-device
./build/bin/llama-ls-sycl-device
```
A example of such log in a system with 1 *intel CPU* and 1 *intel GPU* can look like the following:
```
@ -313,7 +313,7 @@ Examples:
- Use device 0:
```sh
ZES_ENABLE_SYSMAN=1 ./build/bin/main -m models/llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 33 -sm none -mg 0
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -m models/llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 33 -sm none -mg 0
```
or run by script:
@ -324,7 +324,7 @@ or run by script:
- Use multiple devices:
```sh
ZES_ENABLE_SYSMAN=1 ./build/bin/main -m models/llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 33 -sm layer
ZES_ENABLE_SYSMAN=1 ./build/bin/llama-cli -m models/llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 33 -sm layer
```
Otherwise, you can run the script:
@ -427,7 +427,7 @@ Otherwise, run the `win-build-sycl.bat` wrapper which encapsulates the former in
*Notes:*
- By default, calling `make` will build all target binary files. In case of a minimal experimental setup, the user can build the inference executable only through `make main`.
- By default, calling `make` will build all target binary files. In case of a minimal experimental setup, the user can build the inference executable only through `make llama-cli`.
### III. Run the inference
@ -488,13 +488,13 @@ Examples:
- Use device 0:
```
build\bin\main.exe -m models\llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:\nStep 1:" -n 400 -e -ngl 33 -s 0 -sm none -mg 0
build\bin\llama-cli.exe -m models\llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:\nStep 1:" -n 400 -e -ngl 33 -s 0 -sm none -mg 0
```
- Use multiple devices:
```
build\bin\main.exe -m models\llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:\nStep 1:" -n 400 -e -ngl 33 -s 0 -sm layer
build\bin\llama-cli.exe -m models\llama-2-7b.Q4_0.gguf -p "Building a website can be done in 10 simple steps:\nStep 1:" -n 400 -e -ngl 33 -s 0 -sm layer
```
Otherwise, run the following wrapper script:

33
README.md
View File

@ -10,6 +10,9 @@
Inference of Meta's [LLaMA](https://arxiv.org/abs/2302.13971) model (and others) in pure C/C++
> [!IMPORTANT]
[2024 Jun 12] Binaries have been renamed w/ a `llama-` prefix. `main` is now `llama-cli`, `server` is `llama-server`, etc (https://github.com/ggerganov/llama.cpp/pull/7809)
### Recent API changes
- [2024 Apr 21] `llama_token_to_piece` can now optionally render special tokens https://github.com/ggerganov/llama.cpp/pull/6807
@ -217,7 +220,7 @@ Unless otherwise noted these projects are open-source with permissive licensing:
Here is a typical run using LLaMA v2 13B on M2 Ultra:
```
$ make -j && ./main -m models/llama-13b-v2/ggml-model-q4_0.gguf -p "Building a website can be done in 10 simple steps:\nStep 1:" -n 400 -e
$ make -j && ./llama-cli -m models/llama-13b-v2/ggml-model-q4_0.gguf -p "Building a website can be done in 10 simple steps:\nStep 1:" -n 400 -e
I llama.cpp build info:
I UNAME_S: Darwin
I UNAME_P: arm
@ -555,7 +558,7 @@ Building the program with BLAS support may lead to some performance improvements
```sh
# Build the image
docker build -t llama-cpp-vulkan -f .devops/main-vulkan.Dockerfile .
docker build -t llama-cpp-vulkan -f .devops/llama-cli-vulkan.Dockerfile .
# Then, use it:
docker run -it --rm -v "$(pwd):/app:Z" --device /dev/dri/renderD128:/dev/dri/renderD128 --device /dev/dri/card1:/dev/dri/card1 llama-cpp-vulkan -m "/app/models/YOUR_MODEL_FILE" -p "Building a website can be done in 10 simple steps:" -n 400 -e -ngl 33
@ -586,7 +589,7 @@ Building the program with BLAS support may lead to some performance improvements
cmake -B build -DLLAMA_VULKAN=1
cmake --build build --config Release
# Test the output binary (with "-ngl 33" to offload all layers to GPU)
./bin/main -m "PATH_TO_MODEL" -p "Hi you how are you" -n 50 -e -ngl 33 -t 4
./bin/llama-cli -m "PATH_TO_MODEL" -p "Hi you how are you" -n 50 -e -ngl 33 -t 4
# You should see in the output, ggml_vulkan detected your GPU. For example:
# ggml_vulkan: Using Intel(R) Graphics (ADL GT2) | uma: 1 | fp16: 1 | warp size: 32
@ -623,17 +626,17 @@ python3 convert-hf-to-gguf.py models/mymodel/
python convert-hf-to-gguf.py models/mymodel/ --vocab-type bpe
# quantize the model to 4-bits (using Q4_K_M method)
./quantize ./models/mymodel/ggml-model-f16.gguf ./models/mymodel/ggml-model-Q4_K_M.gguf Q4_K_M
./llama-quantize ./models/mymodel/ggml-model-f16.gguf ./models/mymodel/ggml-model-Q4_K_M.gguf Q4_K_M
# update the gguf filetype to current version if older version is now unsupported
./quantize ./models/mymodel/ggml-model-Q4_K_M.gguf ./models/mymodel/ggml-model-Q4_K_M-v2.gguf COPY
./llama-quantize ./models/mymodel/ggml-model-Q4_K_M.gguf ./models/mymodel/ggml-model-Q4_K_M-v2.gguf COPY
```
### Run the quantized model
```bash
# start inference on a gguf model
./main -m ./models/mymodel/ggml-model-Q4_K_M.gguf -n 128
./llama-cli -m ./models/mymodel/ggml-model-Q4_K_M.gguf -n 128
```
When running the larger models, make sure you have enough disk space to store all the intermediate files.
@ -708,7 +711,7 @@ The time per token is measured on a MacBook M1 Pro 32GB RAM using 4 and 8 thread
#### How to run
1. Download/extract: https://huggingface.co/datasets/ggml-org/ci/resolve/main/wikitext-2-raw-v1.zip
2. Run `./perplexity -m models/7B/ggml-model-q4_0.gguf -f wiki.test.raw`
2. Run `./llama-perplexity -m models/7B/ggml-model-q4_0.gguf -f wiki.test.raw`
3. Output:
```
perplexity : calculating perplexity over 655 chunks
@ -732,16 +735,16 @@ Here is an example of a few-shot interaction, invoked with the command
./examples/chat-13B.sh
# custom arguments using a 13B model
./main -m ./models/13B/ggml-model-q4_0.gguf -n 256 --repeat_penalty 1.0 --color -i -r "User:" -f prompts/chat-with-bob.txt
./llama-cli -m ./models/13B/ggml-model-q4_0.gguf -n 256 --repeat_penalty 1.0 --color -i -r "User:" -f prompts/chat-with-bob.txt
```
Note the use of `--color` to distinguish between user input and generated text. Other parameters are explained in more detail in the [README](examples/main/README.md) for the `main` example program.
Note the use of `--color` to distinguish between user input and generated text. Other parameters are explained in more detail in the [README](examples/main/README.md) for the `llama-cli` example program.
![image](https://user-images.githubusercontent.com/1991296/224575029-2af3c7dc-5a65-4f64-a6bb-517a532aea38.png)
### Persistent Interaction
The prompt, user inputs, and model generations can be saved and resumed across calls to `./main` by leveraging `--prompt-cache` and `--prompt-cache-all`. The `./examples/chat-persistent.sh` script demonstrates this with support for long-running, resumable chat sessions. To use this example, you must provide a file to cache the initial chat prompt and a directory to save the chat session, and may optionally provide the same variables as `chat-13B.sh`. The same prompt cache can be reused for new chat sessions. Note that both prompt cache and chat directory are tied to the initial prompt (`PROMPT_TEMPLATE`) and the model file.
The prompt, user inputs, and model generations can be saved and resumed across calls to `./llama-cli` by leveraging `--prompt-cache` and `--prompt-cache-all`. The `./examples/chat-persistent.sh` script demonstrates this with support for long-running, resumable chat sessions. To use this example, you must provide a file to cache the initial chat prompt and a directory to save the chat session, and may optionally provide the same variables as `chat-13B.sh`. The same prompt cache can be reused for new chat sessions. Note that both prompt cache and chat directory are tied to the initial prompt (`PROMPT_TEMPLATE`) and the model file.
```bash
# Start a new chat
@ -763,7 +766,7 @@ PROMPT_TEMPLATE=./prompts/chat-with-bob.txt PROMPT_CACHE_FILE=bob.prompt.bin \
`llama.cpp` supports grammars to constrain model output. For example, you can force the model to output JSON only:
```bash
./main -m ./models/13B/ggml-model-q4_0.gguf -n 256 --grammar-file grammars/json.gbnf -p 'Request: schedule a call at 8pm; Command:'
./llama-cli -m ./models/13B/ggml-model-q4_0.gguf -n 256 --grammar-file grammars/json.gbnf -p 'Request: schedule a call at 8pm; Command:'
```
The `grammars/` folder contains a handful of sample grammars. To write your own, check out the [GBNF Guide](./grammars/README.md).
@ -842,7 +845,7 @@ $mv /sdcard/llama.cpp/llama-2-7b-chat.Q4_K_M.gguf /data/data/com.termux/files/ho
Now, you can start chatting:
```
$cd /data/data/com.termux/files/home/bin
$./main -m ../model/llama-2-7b-chat.Q4_K_M.gguf -n 128 -cml
$./llama-cli -m ../model/llama-2-7b-chat.Q4_K_M.gguf -n 128 -cml
```
Here's a demo of an interactive session running on Pixel 5 phone:
@ -909,8 +912,8 @@ Assuming one has the [nvidia-container-toolkit](https://github.com/NVIDIA/nvidia
```bash
docker build -t local/llama.cpp:full-cuda -f .devops/full-cuda.Dockerfile .
docker build -t local/llama.cpp:light-cuda -f .devops/main-cuda.Dockerfile .
docker build -t local/llama.cpp:server-cuda -f .devops/server-cuda.Dockerfile .
docker build -t local/llama.cpp:light-cuda -f .devops/llama-cli-cuda.Dockerfile .
docker build -t local/llama.cpp:server-cuda -f .devops/llama-server-cuda.Dockerfile .
```
You may want to pass in some different `ARGS`, depending on the CUDA environment supported by your container host, as well as the GPU architecture.
@ -960,7 +963,7 @@ docker run --gpus all -v /path/to/models:/models local/llama.cpp:server-cuda -m
### Docs
- [main](./examples/main/README.md)
- [main (cli)](./examples/main/README.md)
- [server](./examples/server/README.md)
- [jeopardy](./examples/jeopardy/README.md)
- [BLIS](./docs/BLIS.md)

224
ci/run.sh
View File

@ -303,47 +303,47 @@ function gg_run_open_llama_7b_v2 {
wiki_test="${path_wiki}/wiki.test.raw"
./bin/quantize ${model_f16} ${model_q8_0} q8_0
./bin/quantize ${model_f16} ${model_q4_0} q4_0
./bin/quantize ${model_f16} ${model_q4_1} q4_1
./bin/quantize ${model_f16} ${model_q5_0} q5_0
./bin/quantize ${model_f16} ${model_q5_1} q5_1
./bin/quantize ${model_f16} ${model_q2_k} q2_k
./bin/quantize ${model_f16} ${model_q3_k} q3_k
./bin/quantize ${model_f16} ${model_q4_k} q4_k
./bin/quantize ${model_f16} ${model_q5_k} q5_k
./bin/quantize ${model_f16} ${model_q6_k} q6_k
./bin/llama-quantize ${model_f16} ${model_q8_0} q8_0
./bin/llama-quantize ${model_f16} ${model_q4_0} q4_0
./bin/llama-quantize ${model_f16} ${model_q4_1} q4_1
./bin/llama-quantize ${model_f16} ${model_q5_0} q5_0
./bin/llama-quantize ${model_f16} ${model_q5_1} q5_1
./bin/llama-quantize ${model_f16} ${model_q2_k} q2_k
./bin/llama-quantize ${model_f16} ${model_q3_k} q3_k
./bin/llama-quantize ${model_f16} ${model_q4_k} q4_k
./bin/llama-quantize ${model_f16} ${model_q5_k} q5_k
./bin/llama-quantize ${model_f16} ${model_q6_k} q6_k
(time ./bin/main --model ${model_f16} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/main --model ${model_q8_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/main --model ${model_q4_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/main --model ${model_q4_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/main --model ${model_q5_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/main --model ${model_q5_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/main --model ${model_q2_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/main --model ${model_q3_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/main --model ${model_q4_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/main --model ${model_q5_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/main --model ${model_q6_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-cli --model ${model_f16} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-cli --model ${model_q8_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-cli --model ${model_q4_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-cli --model ${model_q4_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-cli --model ${model_q5_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-cli --model ${model_q5_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-cli --model ${model_q2_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-cli --model ${model_q3_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-cli --model ${model_q4_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-cli --model ${model_q5_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-cli --model ${model_q6_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/perplexity --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/perplexity --model ${model_q8_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/perplexity --model ${model_q4_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/perplexity --model ${model_q4_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/perplexity --model ${model_q5_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/perplexity --model ${model_q5_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/perplexity --model ${model_q2_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/perplexity --model ${model_q3_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/perplexity --model ${model_q4_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/perplexity --model ${model_q5_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/perplexity --model ${model_q6_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-perplexity --model ${model_q4_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-perplexity --model ${model_q4_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-perplexity --model ${model_q5_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-perplexity --model ${model_q5_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-perplexity --model ${model_q2_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-perplexity --model ${model_q3_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-perplexity --model ${model_q4_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-perplexity --model ${model_q5_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-perplexity --model ${model_q6_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/imatrix --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/save-load-state -ngl 10 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/save-load-state -fa -ngl 10 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/save-load-state -ngl 99 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/save-load-state -fa -ngl 99 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -ngl 10 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -fa -ngl 10 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -ngl 99 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -fa -ngl 99 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
function check_ppl {
qnt="$1"
@ -437,45 +437,45 @@ function gg_run_pythia_1_4b {
wiki_test_60="${path_wiki}/wiki.test-60.raw"
./bin/quantize ${model_f16} ${model_q8_0} q8_0
./bin/quantize ${model_f16} ${model_q4_0} q4_0
./bin/quantize ${model_f16} ${model_q4_1} q4_1
./bin/quantize ${model_f16} ${model_q5_0} q5_0
./bin/quantize ${model_f16} ${model_q5_1} q5_1
./bin/quantize ${model_f16} ${model_q2_k} q2_k
./bin/quantize ${model_f16} ${model_q3_k} q3_k
./bin/quantize ${model_f16} ${model_q4_k} q4_k
./bin/quantize ${model_f16} ${model_q5_k} q5_k
./bin/quantize ${model_f16} ${model_q6_k} q6_k
./bin/llama-quantize ${model_f16} ${model_q8_0} q8_0
./bin/llama-quantize ${model_f16} ${model_q4_0} q4_0
./bin/llama-quantize ${model_f16} ${model_q4_1} q4_1
./bin/llama-quantize ${model_f16} ${model_q5_0} q5_0
./bin/llama-quantize ${model_f16} ${model_q5_1} q5_1
./bin/llama-quantize ${model_f16} ${model_q2_k} q2_k
./bin/llama-quantize ${model_f16} ${model_q3_k} q3_k
./bin/llama-quantize ${model_f16} ${model_q4_k} q4_k
./bin/llama-quantize ${model_f16} ${model_q5_k} q5_k
./bin/llama-quantize ${model_f16} ${model_q6_k} q6_k
(time ./bin/main --model ${model_f16} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/main --model ${model_q8_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/main --model ${model_q4_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/main --model ${model_q4_1} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/main --model ${model_q5_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/main --model ${model_q5_1} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/main --model ${model_q2_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/main --model ${model_q3_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/main --model ${model_q4_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/main --model ${model_q5_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/main --model ${model_q6_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-cli --model ${model_f16} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-cli --model ${model_q8_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-cli --model ${model_q4_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-cli --model ${model_q4_1} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-cli --model ${model_q5_0} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-cli --model ${model_q5_1} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-cli --model ${model_q2_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-cli --model ${model_q3_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-cli --model ${model_q4_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-cli --model ${model_q5_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-cli --model ${model_q6_k} -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/perplexity --model ${model_f16} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/perplexity --model ${model_q8_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/perplexity --model ${model_q4_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/perplexity --model ${model_q4_1} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/perplexity --model ${model_q5_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/perplexity --model ${model_q5_1} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/perplexity --model ${model_q2_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/perplexity --model ${model_q3_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/perplexity --model ${model_q4_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/perplexity --model ${model_q5_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/perplexity --model ${model_q6_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-perplexity --model ${model_q4_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-perplexity --model ${model_q4_1} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-perplexity --model ${model_q5_0} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-perplexity --model ${model_q5_1} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-perplexity --model ${model_q2_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-perplexity --model ${model_q3_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-perplexity --model ${model_q4_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-perplexity --model ${model_q5_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-perplexity --model ${model_q6_k} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/imatrix --model ${model_f16} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test_60} -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/save-load-state --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/save-load-state -fa --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -fa --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
function check_ppl {
qnt="$1"
@ -569,47 +569,47 @@ function gg_run_pythia_2_8b {
wiki_test="${path_wiki}/wiki.test.raw"
./bin/quantize ${model_f16} ${model_q8_0} q8_0
./bin/quantize ${model_f16} ${model_q4_0} q4_0
./bin/quantize ${model_f16} ${model_q4_1} q4_1
./bin/quantize ${model_f16} ${model_q5_0} q5_0
./bin/quantize ${model_f16} ${model_q5_1} q5_1
./bin/quantize ${model_f16} ${model_q2_k} q2_k
./bin/quantize ${model_f16} ${model_q3_k} q3_k
./bin/quantize ${model_f16} ${model_q4_k} q4_k
./bin/quantize ${model_f16} ${model_q5_k} q5_k
./bin/quantize ${model_f16} ${model_q6_k} q6_k
./bin/llama-quantize ${model_f16} ${model_q8_0} q8_0
./bin/llama-quantize ${model_f16} ${model_q4_0} q4_0
./bin/llama-quantize ${model_f16} ${model_q4_1} q4_1
./bin/llama-quantize ${model_f16} ${model_q5_0} q5_0
./bin/llama-quantize ${model_f16} ${model_q5_1} q5_1
./bin/llama-quantize ${model_f16} ${model_q2_k} q2_k
./bin/llama-quantize ${model_f16} ${model_q3_k} q3_k
./bin/llama-quantize ${model_f16} ${model_q4_k} q4_k
./bin/llama-quantize ${model_f16} ${model_q5_k} q5_k
./bin/llama-quantize ${model_f16} ${model_q6_k} q6_k
(time ./bin/main --model ${model_f16} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/main --model ${model_q8_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/main --model ${model_q4_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/main --model ${model_q4_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/main --model ${model_q5_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/main --model ${model_q5_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/main --model ${model_q2_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/main --model ${model_q3_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/main --model ${model_q4_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/main --model ${model_q5_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/main --model ${model_q6_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-cli --model ${model_f16} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-cli --model ${model_q8_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-cli --model ${model_q4_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-cli --model ${model_q4_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-cli --model ${model_q5_0} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-cli --model ${model_q5_1} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-cli --model ${model_q2_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-cli --model ${model_q3_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-cli --model ${model_q4_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-cli --model ${model_q5_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-cli --model ${model_q6_k} -t 1 -ngl 999 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/perplexity --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/perplexity --model ${model_q8_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/perplexity --model ${model_q4_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/perplexity --model ${model_q4_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/perplexity --model ${model_q5_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/perplexity --model ${model_q5_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/perplexity --model ${model_q2_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/perplexity --model ${model_q3_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/perplexity --model ${model_q4_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/perplexity --model ${model_q5_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/perplexity --model ${model_q6_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-perplexity --model ${model_q4_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-perplexity --model ${model_q4_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-perplexity --model ${model_q5_0} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-perplexity --model ${model_q5_1} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-perplexity --model ${model_q2_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-perplexity --model ${model_q3_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-perplexity --model ${model_q4_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-perplexity --model ${model_q5_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-perplexity --model ${model_q6_k} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/imatrix --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test} -t 1 -ngl 999 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/save-load-state -ngl 10 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/save-load-state -fa -ngl 10 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/save-load-state -ngl 99 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/save-load-state -fa -ngl 99 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -ngl 10 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -fa -ngl 10 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -ngl 99 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state -fa -ngl 99 --model ${model_q4_0} ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
function check_ppl {
qnt="$1"
@ -693,10 +693,10 @@ function gg_run_embd_bge_small {
model_f16="${path_models}/ggml-model-f16.gguf"
model_q8_0="${path_models}/ggml-model-q8_0.gguf"
./bin/quantize ${model_f16} ${model_q8_0} q8_0
./bin/llama-quantize ${model_f16} ${model_q8_0} q8_0
(time ./bin/embedding --model ${model_f16} -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/embedding --model ${model_q8_0} -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-embedding --model ${model_f16} -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-embedding --model ${model_q8_0} -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
set +e
}

2
docs/HOWTO-add-model.md
View File

@ -100,7 +100,7 @@ Have a look at existing implementation like `build_llama`, `build_dbrx` or `buil
When implementing a new graph, please note that the underlying `ggml` backends might not support them all, support for missing backend operations can be added in another PR.
Note: to debug the inference graph: you can use [eval-callback](../examples/eval-callback).
Note: to debug the inference graph: you can use [llama-eval-callback](../examples/eval-callback).
## GGUF specification

4
docs/token_generation_performance_tips.md
View File

@ -3,7 +3,7 @@
## Verifying that the model is running on the GPU with CUDA
Make sure you compiled llama with the correct env variables according to [this guide](../README.md#CUDA), so that llama accepts the `-ngl N` (or `--n-gpu-layers N`) flag. When running llama, you may configure `N` to be very large, and llama will offload the maximum possible number of layers to the GPU, even if it's less than the number you configured. For example:
```shell
./main -m "path/to/model.gguf" -ngl 200000 -p "Please sir, may I have some "
./llama-cli -m "path/to/model.gguf" -ngl 200000 -p "Please sir, may I have some "
```
When running llama, before it starts the inference work, it will output diagnostic information that shows whether cuBLAS is offloading work to the GPU. Look for these lines:
@ -27,7 +27,7 @@ RAM: 32GB
Model: `TheBloke_Wizard-Vicuna-30B-Uncensored-GGML/Wizard-Vicuna-30B-Uncensored.q4_0.gguf` (30B parameters, 4bit quantization, GGML)
Run command: `./main -m "path/to/model.gguf" -p "An extremely detailed description of the 10 best ethnic dishes will follow, with recipes: " -n 1000 [additional benchmark flags]`
Run command: `./llama-cli -m "path/to/model.gguf" -p "An extremely detailed description of the 10 best ethnic dishes will follow, with recipes: " -n 1000 [additional benchmark flags]`
Result:

47
examples/CMakeLists.txt
View File

@ -13,42 +13,43 @@ include_directories(${CMAKE_CURRENT_SOURCE_DIR})
if (EMSCRIPTEN)
else()
add_subdirectory(baby-llama)
add_subdirectory(batched)
add_subdirectory(batched-bench)
add_subdirectory(batched)
add_subdirectory(benchmark)
add_subdirectory(convert-llama2c-to-ggml)
add_subdirectory(embedding)
add_subdirectory(eval-callback)
add_subdirectory(export-lora)
add_subdirectory(finetune)
add_subdirectory(gritlm)
add_subdirectory(gbnf-validator)
add_subdirectory(gguf-split)
add_subdirectory(gguf)
add_subdirectory(gritlm)
add_subdirectory(imatrix)
add_subdirectory(infill)
add_subdirectory(llama-bench)
add_subdirectory(llava)
if (LLAMA_SYCL)
add_subdirectory(sycl)
endif()
add_subdirectory(main)
add_subdirectory(tokenize)
add_subdirectory(parallel)
add_subdirectory(perplexity)
add_subdirectory(quantize)
add_subdirectory(quantize-stats)
add_subdirectory(retrieval)
add_subdirectory(save-load-state)
add_subdirectory(simple)
add_subdirectory(passkey)
add_subdirectory(speculative)
add_subdirectory(lookahead)
add_subdirectory(lookup)
add_subdirectory(gguf)
add_subdirectory(train-text-from-scratch)
add_subdirectory(imatrix)
if (LLAMA_BUILD_SERVER)
add_subdirectory(server)
endif()
add_subdirectory(export-lora)
add_subdirectory(main)
add_subdirectory(parallel)
add_subdirectory(passkey)
add_subdirectory(perplexity)
add_subdirectory(quantize-stats)
add_subdirectory(quantize)
add_subdirectory(retrieval)
if (LLAMA_RPC)
add_subdirectory(rpc)
endif()
if (LLAMA_BUILD_SERVER)
add_subdirectory(server)
endif()
if (LLAMA_SYCL)
add_subdirectory(sycl)
endif()
add_subdirectory(save-load-state)
add_subdirectory(simple)
add_subdirectory(speculative)
add_subdirectory(tokenize)
add_subdirectory(train-text-from-scratch)
endif()

2
examples/Miku.sh
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@ -22,7 +22,7 @@ if [ -n "$N_THREAD" ]; then
GEN_OPTIONS+=(--threads "$N_THREAD")
fi
./main "${GEN_OPTIONS[@]}" \
./llama-cli "${GEN_OPTIONS[@]}" \
--model "$MODEL" \
--in-prefix " " \
--in-suffix "${AI_NAME}:" \

2
examples/baby-llama/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET baby-llama)
set(TARGET llama-baby-llama)
add_executable(${TARGET} baby-llama.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

2
examples/base-translate.sh
View File

@ -58,4 +58,4 @@ echo "$2
model=$1
# generate the most likely continuation until the string "===" is found
./main -m $model -f $ftmp -n 64 --temp 0 --repeat-penalty 1.0 --no-penalize-nl -r "===" $eargs
./llama-cli -m $model -f $ftmp -n 64 --temp 0 --repeat-penalty 1.0 --no-penalize-nl -r "===" $eargs

2
examples/batched-bench/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET batched-bench)
set(TARGET llama-batched-bench)
add_executable(${TARGET} batched-bench.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

8
examples/batched-bench/README.md
View File

@ -10,16 +10,16 @@ There are 2 modes of operation:
- `prompt is shared` - there is a common prompt of size `PP` used by all batches (i.e. `N_KV = PP + B*TG`)
```bash
./batched-bench -m model.gguf -c 2048 -b 2048 -ub 512 -npp 128,256,512 -ntg 128,256 -npl 1,2,4,8,16,32 [-pps]
./llama-batched-bench -m model.gguf -c 2048 -b 2048 -ub 512 -npp 128,256,512 -ntg 128,256 -npl 1,2,4,8,16,32 [-pps]
# LLaMA 7B, F16, N_KV_MAX = 16384 (8GB), prompt not shared
./batched-bench -m ./models/llama-7b/ggml-model-f16.gguf -c 16384 -b 2048 -ub 512 -ngl 99
./llama-batched-bench -m ./models/llama-7b/ggml-model-f16.gguf -c 16384 -b 2048 -ub 512 -ngl 99
# LLaMA 7B, Q8_0, N_KV_MAX = 16384 (8GB), prompt is shared
./batched-bench -m ./models/llama-7b/ggml-model-q8_0.gguf -c 16384 -b 2048 -ub 512 -ngl 99 -pps
./llama-batched-bench -m ./models/llama-7b/ggml-model-q8_0.gguf -c 16384 -b 2048 -ub 512 -ngl 99 -pps
# custom set of batches
./batched-bench -m ./models/llama-7b/ggml-model-q8_0.gguf -c 2048 -b 512 -ub 512 -ngl 999 -npp 128,256,512 -ntg 128,256 -npl 1,2,4,8,16,32
./llama-batched-bench -m ./models/llama-7b/ggml-model-q8_0.gguf -c 2048 -b 512 -ub 512 -ngl 999 -npp 128,256,512 -ntg 128,256 -npl 1,2,4,8,16,32
```
## Sample results

6
examples/batched.swift/Makefile
View File

@ -1,6 +1,6 @@
.PHONY: build
build:
xcodebuild -scheme batched_swift -destination "generic/platform=macOS" -derivedDataPath build
rm -f ./batched_swift
ln -s ./build/Build/Products/Debug/batched_swift ./batched_swift
xcodebuild -scheme llama-batched-swift -destination "generic/platform=macOS" -derivedDataPath build
rm -f ./llama-batched-swift
ln -s ./build/Build/Products/Debug/llama-batched-swift ./llama-batched-swift

4
examples/batched.swift/Package.swift
View File

@ -4,7 +4,7 @@
import PackageDescription
let package = Package(
name: "batched_swift",
name: "llama-batched-swift",
platforms: [.macOS(.v12)],
dependencies: [
.package(name: "llama", path: "../../"),
@ -13,7 +13,7 @@ let package = Package(
// Targets are the basic building blocks of a package, defining a module or a test suite.
// Targets can depend on other targets in this package and products from dependencies.
.executableTarget(
name: "batched_swift",
name: "llama-batched-swift",
dependencies: ["llama"],
path: "Sources",
linkerSettings: [.linkedFramework("Foundation"), .linkedFramework("AppKit")]

2
examples/batched.swift/README.md
View File

@ -1,4 +1,4 @@
This is a swift clone of `examples/batched`.
$ `make`
$ `./batched_swift MODEL_PATH [PROMPT] [PARALLEL]`
$ `./llama-batched-swift MODEL_PATH [PROMPT] [PARALLEL]`

2
examples/batched/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET batched)
set(TARGET llama-batched)
add_executable(${TARGET} batched.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

2
examples/batched/README.md
View File

@ -3,7 +3,7 @@
The example demonstrates batched generation from a given prompt
```bash
./batched -m ./models/llama-7b-v2/ggml-model-f16.gguf -p "Hello my name is" -np 4
./llama-batched -m ./models/llama-7b-v2/ggml-model-f16.gguf -p "Hello my name is" -np 4
...

2
examples/benchmark/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET benchmark)
set(TARGET llama-bench-matmult)
add_executable(${TARGET} benchmark-matmult.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE llama build_info ${CMAKE_THREAD_LIBS_INIT})

2
examples/chat-13B.sh
View File

@ -30,7 +30,7 @@ sed -e "s/\[\[USER_NAME\]\]/$USER_NAME/g" \
$PROMPT_TEMPLATE > $PROMPT_FILE
# shellcheck disable=SC2086 # Intended splitting of GEN_OPTIONS
./main $GEN_OPTIONS \
./llama-cli $GEN_OPTIONS \
--model "$MODEL" \
--threads "$N_THREAD" \
--n_predict "$N_PREDICTS" \

10
examples/chat-persistent.sh
View File

@ -62,7 +62,7 @@ fi
if [[ ! -e "$PROMPT_CACHE_FILE" ]]; then
echo 'Prompt cache does not exist, building...'
# Default batch_size to 64 here for better user feedback during initial prompt processing
./main 2>>"$LOG" \
./llama-cli 2>>"$LOG" \
--batch_size 64 \
"${OPTS[@]}" \
--prompt-cache "$PROMPT_CACHE_FILE" \
@ -109,13 +109,13 @@ while read -e line; do
printf '%s: ' "$AI_NAME" >>"$CUR_PROMPT_FILE"
./main 2>>"$LOG" "${OPTS[@]}" \
./llama-cli 2>>"$LOG" "${OPTS[@]}" \
--prompt-cache "$CUR_PROMPT_CACHE" \
--prompt-cache-all \
--file "$CUR_PROMPT_FILE" \
--reverse-prompt "${USER_NAME}:" \
--n_predict "$n_predict" |
skip_bytes 1 | # skip BOS token added by ./main
skip_bytes 1 | # skip BOS token added by ./llama-cli
tee "$CUR_PROMPT_FILE.tmp" | # save prompt + generation to tmp file
skip_bytes "$n_prompt_len_pre" # print generation
@ -133,7 +133,7 @@ while read -e line; do
# TODO get both messages in one go
if ! session_size_msg="$(tail -n30 "$LOG" | grep -oE "$SESSION_SIZE_MSG_PATTERN")" ||
! sample_time_msg="$(tail -n10 "$LOG" | grep -oE "$SAMPLE_TIME_MSG_PATTERN")"; then
echo >&2 "Couldn't get number of tokens from ./main output!"
echo >&2 "Couldn't get number of tokens from ./llama-cli output!"
exit 1
fi
@ -144,7 +144,7 @@ while read -e line; do
fi
# Update cache for next prompt in background, ideally during user input
./main >>"$LOG_BG" 2>&1 "${OPTS[@]}" \
./llama-cli >>"$LOG_BG" 2>&1 "${OPTS[@]}" \
--prompt-cache "$NEXT_PROMPT_CACHE" \
--file "$NEXT_PROMPT_FILE" \
--n_predict 1 &

2
examples/chat-vicuna.sh
View File

@ -30,7 +30,7 @@ sed -e "s/\[\[USER_NAME\]\]/$USER_NAME/g" \
$PROMPT_TEMPLATE > $PROMPT_FILE
# shellcheck disable=SC2086 # Intended splitting of GEN_OPTIONS
./bin/main $GEN_OPTIONS \
./bin/llama-cli $GEN_OPTIONS \
--model "$MODEL" \
--threads "$N_THREAD" \
--n_predict "$N_PREDICTS" \

2
examples/chat.sh
View File

@ -11,6 +11,6 @@ cd ..
#
# "--keep 48" is based on the contents of prompts/chat-with-bob.txt
#
./main -m ./models/llama-7b/ggml-model-q4_0.gguf -c 512 -b 1024 -n 256 --keep 48 \
./llama-cli -m ./models/llama-7b/ggml-model-q4_0.gguf -c 512 -b 1024 -n 256 --keep 48 \
--repeat_penalty 1.0 --color -i \
-r "User:" -f prompts/chat-with-bob.txt

2
examples/convert-llama2c-to-ggml/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET convert-llama2c-to-ggml)
set(TARGET llama-convert-llama2c-to-ggml)
add_executable(${TARGET} convert-llama2c-to-ggml.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

6
examples/convert-llama2c-to-ggml/README.md
View File

@ -8,7 +8,7 @@ To convert the model first download the models from the [llama2.c](https://githu
After successful compilation, following usage options are available:
```
usage: ./convert-llama2c-to-ggml [options]
usage: ./llama-convert-llama2c-to-ggml [options]
options:
-h, --help show this help message and exit
@ -19,10 +19,10 @@ options:
An example command using a model from [karpathy/tinyllamas](https://huggingface.co/karpathy/tinyllamas) is as follows:
`$ ./convert-llama2c-to-ggml --copy-vocab-from-model llama-2-7b-chat.gguf.q2_K.bin --llama2c-model stories42M.bin --llama2c-output-model stories42M.gguf.bin`
`$ ./llama-convert-llama2c-to-ggml --copy-vocab-from-model llama-2-7b-chat.gguf.q2_K.bin --llama2c-model stories42M.bin --llama2c-output-model stories42M.gguf.bin`
Note: The vocabulary for `stories260K.bin` should be its own tokenizer `tok512.bin` found in [karpathy/tinyllamas/stories260K](https://huggingface.co/karpathy/tinyllamas/tree/main/stories260K).
Now you can use the model with a command like:
`$ ./main -m stories42M.gguf.bin -p "One day, Lily met a Shoggoth" -n 500 -c 256`
`$ ./llama-cli -m stories42M.gguf.bin -p "One day, Lily met a Shoggoth" -n 500 -c 256`

2
examples/embedding/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET embedding)
set(TARGET llama-embedding)
add_executable(${TARGET} embedding.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

4
examples/embedding/README.md
View File

@ -9,13 +9,13 @@ To get started right away, run the following command, making sure to use the cor
### Unix-based systems (Linux, macOS, etc.):
```bash
./embedding -m ./path/to/model --log-disable -p "Hello World!" 2>/dev/null
./llama-embedding -m ./path/to/model --log-disable -p "Hello World!" 2>/dev/null
```
### Windows:
```powershell
embedding.exe -m ./path/to/model --log-disable -p "Hello World!" 2>$null
llama-embedding.exe -m ./path/to/model --log-disable -p "Hello World!" 2>$null
```
The above command will output space-separated float values.

4
examples/eval-callback/CMakeLists.txt
View File

@ -1,9 +1,9 @@
set(TARGET eval-callback)
set(TARGET llama-eval-callback)
add_executable(${TARGET} eval-callback.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
target_compile_features(${TARGET} PRIVATE cxx_std_11)
set(TEST_TARGET test-eval-callback)
add_test(NAME ${TEST_TARGET} COMMAND eval-callback --hf-repo ggml-org/models --hf-file tinyllamas/stories260K.gguf --model stories260K.gguf --prompt hello --seed 42 -ngl 0)
add_test(NAME ${TEST_TARGET} COMMAND llama-eval-callback --hf-repo ggml-org/models --hf-file tinyllamas/stories260K.gguf --model stories260K.gguf --prompt hello --seed 42 -ngl 0)
set_property(TEST ${TEST_TARGET} PROPERTY LABELS eval-callback curl)

2
examples/eval-callback/README.md
View File

@ -6,7 +6,7 @@ It simply prints to the console all operations and tensor data.
Usage:
```shell
eval-callback \
llama-eval-callback \
--hf-repo ggml-org/models \
--hf-file phi-2/ggml-model-q4_0.gguf \
--model phi-2-q4_0.gguf \

2
examples/export-lora/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET export-lora)
set(TARGET llama-export-lora)
add_executable(${TARGET} export-lora.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

4
examples/export-lora/README.md
View File

@ -3,7 +3,7 @@
Apply LORA adapters to base model and export the resulting model.
```
usage: export-lora [options]
usage: llama-export-lora [options]
options:
-h, --help show this help message and exit
@ -17,7 +17,7 @@ options:
For example:
```bash
./bin/export-lora \
./bin/llama-export-lora \
-m open-llama-3b-v2-q8_0.gguf \
-o open-llama-3b-v2-q8_0-english2tokipona-chat.gguf \
-l lora-open-llama-3b-v2-q8_0-english2tokipona-chat-LATEST.bin

2
examples/finetune/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET finetune)
set(TARGET llama-finetune)
add_executable(${TARGET} finetune.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

12
examples/finetune/README.md
View File

@ -7,7 +7,7 @@ Basic usage instructions:
wget https://raw.githubusercontent.com/brunoklein99/deep-learning-notes/master/shakespeare.txt
# finetune LORA adapter
./bin/finetune \
./bin/llama-finetune \
--model-base open-llama-3b-v2-q8_0.gguf \
--checkpoint-in chk-lora-open-llama-3b-v2-q8_0-shakespeare-LATEST.gguf \
--checkpoint-out chk-lora-open-llama-3b-v2-q8_0-shakespeare-ITERATION.gguf \
@ -18,7 +18,7 @@ wget https://raw.githubusercontent.com/brunoklein99/deep-learning-notes/master/s
--use-checkpointing
# predict
./bin/main -m open-llama-3b-v2-q8_0.gguf --lora lora-open-llama-3b-v2-q8_0-shakespeare-LATEST.bin
./bin/llama-cli -m open-llama-3b-v2-q8_0.gguf --lora lora-open-llama-3b-v2-q8_0-shakespeare-LATEST.bin
```
**Only llama based models are supported!** The output files will be saved every N iterations (config with `--save-every N`).
@ -38,14 +38,14 @@ After 10 more iterations:
Checkpoint files (`--checkpoint-in FN`, `--checkpoint-out FN`) store the training process. When the input checkpoint file does not exist, it will begin finetuning a new randomly initialized adapter.
llama.cpp compatible LORA adapters will be saved with filename specified by `--lora-out FN`.
These LORA adapters can then be used by `main` together with the base model, like in the 'predict' example command above.
These LORA adapters can then be used by `llama-cli` together with the base model, like in the 'predict' example command above.
In `main` you can also load multiple LORA adapters, which will then be mixed together.
In `llama-cli` you can also load multiple LORA adapters, which will then be mixed together.
For example if you have two LORA adapters `lora-open-llama-3b-v2-q8_0-shakespeare-LATEST.bin` and `lora-open-llama-3b-v2-q8_0-bible-LATEST.bin`, you can mix them together like this:
```bash
./bin/main -m open-llama-3b-v2-q8_0.gguf \
./bin/llama-cli -m open-llama-3b-v2-q8_0.gguf \
--lora lora-open-llama-3b-v2-q8_0-shakespeare-LATEST.bin \
--lora lora-open-llama-3b-v2-q8_0-bible-LATEST.bin
```
@ -55,7 +55,7 @@ You can change how strong each LORA adapter is applied to the base model by usin
For example to apply 40% of the 'shakespeare' LORA adapter, 80% of the 'bible' LORA adapter and 100% of yet another one:
```bash
./bin/main -m open-llama-3b-v2-q8_0.gguf \
./bin/llama-cli -m open-llama-3b-v2-q8_0.gguf \
--lora-scaled lora-open-llama-3b-v2-q8_0-shakespeare-LATEST.bin 0.4 \
--lora-scaled lora-open-llama-3b-v2-q8_0-bible-LATEST.bin 0.8 \
--lora lora-open-llama-3b-v2-q8_0-yet-another-one-LATEST.bin

2
examples/finetune/finetune.sh
View File

@ -2,7 +2,7 @@
cd `dirname $0`
cd ../..
EXE="./finetune"
EXE="./llama-finetune"
if [[ ! $LLAMA_MODEL_DIR ]]; then LLAMA_MODEL_DIR="./models"; fi
if [[ ! $LLAMA_TRAINING_DIR ]]; then LLAMA_TRAINING_DIR="."; fi

4
examples/gbnf-validator/CMakeLists.txt
View File

@ -1,5 +1,5 @@
set(TARGET gbnf-validator)
set(TARGET llama-gbnf-validator)
add_executable(${TARGET} gbnf-validator.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common grammar-parser llama ${CMAKE_THREAD_LIBS_INIT})
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
target_compile_features(${TARGET} PRIVATE cxx_std_11)

36
examples/gbnf-validator/gbnf-validator.cpp
View File

@ -7,6 +7,8 @@
#include <cstdio>
#include <cstdlib>
#include <sstream>
#include <fstream>
#include <string>
#include <vector>
@ -69,13 +71,14 @@ int main(int argc, char** argv) {
return 1;
}
fseek(grammar_file, 0, SEEK_END);
size_t grammar_size = ftell(grammar_file);
fseek(grammar_file, 0, SEEK_SET);
std::string grammar_str(grammar_size, ' ');
fread(&grammar_str[0], 1, grammar_size, grammar_file);
fclose(grammar_file);
std::string grammar_str;
{
std::ifstream grammar_file(grammar_filename);
GGML_ASSERT(grammar_file.is_open() && "Failed to open grammar file");
std::stringstream buffer;
buffer << grammar_file.rdbuf();
grammar_str = buffer.str();
}
// Parse the GBNF grammar
auto parsed_grammar = grammar_parser::parse(grammar_str.c_str());
@ -100,20 +103,15 @@ int main(int argc, char** argv) {
grammar_rules.size(), parsed_grammar.symbol_ids.at("root"));
// Read the input file
FILE* input_file = fopen(input_filename.c_str(), "r");
if (!input_file) {
fprintf(stdout, "Failed to open input file: %s\n", input_filename.c_str());
return 1;
std::string input_str;
{
std::ifstream input_file(input_filename);
GGML_ASSERT(input_file.is_open() && "Failed to open input file");
std::stringstream buffer;
buffer << input_file.rdbuf();
input_str = buffer.str();
}
fseek(input_file, 0, SEEK_END);
size_t input_size = ftell(input_file);
fseek(input_file, 0, SEEK_SET);
std::string input_str(input_size, ' ');
fread(&input_str[0], 1, input_size, input_file);
fclose(input_file);
// Validate the input string against the grammar
size_t error_pos;
std::string error_msg;

2
examples/gguf-split/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET gguf-split)
set(TARGET llama-gguf-split)
add_executable(${TARGET} gguf-split.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

4
examples/gguf-split/tests.sh
View File

@ -18,8 +18,8 @@ fi
set -x
SPLIT=$1/gguf-split
MAIN=$1/main
SPLIT=$1/llama-gguf-split
MAIN=$1/llama-cli
WORK_PATH=$TMP_DIR/gguf-split
ROOT_DIR=$(realpath $(dirname $0)/../../)

2
examples/gguf/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET gguf)
set(TARGET llama-gguf)
add_executable(${TARGET} gguf.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE ggml ${CMAKE_THREAD_LIBS_INIT})

2
examples/gritlm/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET gritlm)
set(TARGET llama-gritlm)
add_executable(${TARGET} gritlm.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

2
examples/gritlm/README.md
View File

@ -26,7 +26,7 @@ $ scripts/hf.sh --repo cohesionet/GritLM-7B_gguf --file gritlm-7b_q4_1.gguf --ou
Run the example using the downloaded model:
```console
$ ./gritlm -m models/gritlm-7b_q4_1.gguf
$ ./llama-gritlm -m models/gritlm-7b_q4_1.gguf
Cosine similarity between "Bitcoin: A Peer-to-Peer Electronic Cash System" and "A purely peer-to-peer version of electronic cash w" is: 0.605
Cosine similarity between "Bitcoin: A Peer-to-Peer Electronic Cash System" and "All text-based language problems can be reduced to" is: 0.103

2
examples/imatrix/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET imatrix)
set(TARGET llama-imatrix)
add_executable(${TARGET} imatrix.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

6
examples/imatrix/README.md
View File

@ -6,7 +6,7 @@ More information is available here: https://github.com/ggerganov/llama.cpp/pull/
## Usage
```
./imatrix \
./llama-imatrix \
-m model.gguf -f some-text.txt [-o imatrix.dat] [--process-output] [--verbosity 1] \
[--no-ppl] [--chunk 123] [--output-frequency 10] [--save-frequency 0] \
[--in-file imatrix-prev-0.dat --in-file imatrix-prev-1.dat ...]
@ -28,8 +28,8 @@ For faster computation, make sure to use GPU offloading via the `-ngl` argument
LLAMA_CUDA=1 make -j
# generate importance matrix (imatrix.dat)
./imatrix -m ggml-model-f16.gguf -f train-data.txt -ngl 99
./llama-imatrix -m ggml-model-f16.gguf -f train-data.txt -ngl 99
# use the imatrix to perform a Q4_K_M quantization
./quantize --imatrix imatrix.dat ggml-model-f16.gguf ./ggml-model-q4_k_m.gguf q4_k_m
./llama-quantize --imatrix imatrix.dat ggml-model-f16.gguf ./ggml-model-q4_k_m.gguf q4_k_m
```

2
examples/infill/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET infill)
set(TARGET llama-infill)
add_executable(${TARGET} infill.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

2
examples/infill/README.md
View File

@ -42,5 +42,5 @@ scripts/hf.sh --repo TheBloke/CodeLlama-13B-GGUF --file codellama-13b.Q5_K_S.ggu
```
```bash
./infill -t 10 -ngl 0 -m models/codellama-13b.Q5_K_S.gguf -c 4096 --temp 0.7 --repeat_penalty 1.1 -n 20 --in-prefix "def helloworld():\n print(\"hell" --in-suffix "\n print(\"goodbye world\")\n "
./llama-infill -t 10 -ngl 0 -m models/codellama-13b.Q5_K_S.gguf -c 4096 --temp 0.7 --repeat_penalty 1.1 -n 20 --in-prefix "def helloworld():\n print(\"hell" --in-suffix "\n print(\"goodbye world\")\n "
```

2
examples/jeopardy/jeopardy.sh
View File

@ -21,7 +21,7 @@ counter=1
echo 'Running'
while IFS= read -r question
do
exe_cmd="./main -p "\"$prefix$introduction$nl$prefix$question\"" "$opts" -m ""\"$MODEL\""" >> ""\"$output_file\""
exe_cmd="./llama-cli -p "\"$prefix$introduction$nl$prefix$question\"" "$opts" -m ""\"$MODEL\""" >> ""\"$output_file\""
echo $counter
echo "Current Question: $question"
eval "$exe_cmd"

2
examples/json-schema-pydantic-example.py
View File

@ -1,5 +1,5 @@
# Usage:
#! ./server -m some-model.gguf &
#! ./llama-server -m some-model.gguf &
#! pip install pydantic
#! python json-schema-pydantic-example.py

2
examples/json_schema_to_grammar.py
View File

@ -523,7 +523,7 @@ class SchemaConverter:
def main(args_in = None):
parser = argparse.ArgumentParser(
description='''
Generates a grammar (suitable for use in ./main) that produces JSON conforming to a
Generates a grammar (suitable for use in ./llama-cli) that produces JSON conforming to a
given JSON schema. Only a subset of JSON schema features are supported; more may be
added in the future.
''',

2
examples/llama-bench/README.md
View File

@ -1,4 +1,4 @@
# llama.cpp/example/llama-bench
# llama.cpp/examples/llama-bench
Performance testing tool for llama.cpp.

11
examples/llava/CMakeLists.txt
View File

@ -30,8 +30,9 @@ if(TARGET BUILD_INFO)
add_dependencies(llava BUILD_INFO)
endif()
set(TARGET llava-cli)
add_executable(llava-cli llava-cli.cpp)
install(TARGETS llava-cli RUNTIME)
target_link_libraries(llava-cli PRIVATE common llava ${CMAKE_THREAD_LIBS_INIT})
target_compile_features(llava PRIVATE cxx_std_11)
set(TARGET llama-llava-cli)
add_executable(${TARGET} llava-cli.cpp)
set_target_properties(${TARGET} PROPERTIES OUTPUT_NAME llama-llava-cli)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llava ${CMAKE_THREAD_LIBS_INIT})
target_compile_features(${TARGET} PRIVATE cxx_std_11)

18
examples/llava/MobileVLM-README.md
View File

@ -9,12 +9,12 @@ The implementation is based on llava, and is compatible with llava and mobileVLM
Notice: The overall process of model inference for both **MobileVLM** and **MobileVLM_V2** models is the same, but the process of model conversion is a little different. Therefore, using **MobileVLM-1.7B** as an example, the different conversion step will be shown.
## Usage
Build with cmake or run `make llava-cli` to build it.
Build with cmake or run `make llama-llava-cli` to build it.
After building, run: `./llava-cli` to see the usage. For example:
After building, run: `./llama-llava-cli` to see the usage. For example:
```sh
./llava-cli -m MobileVLM-1.7B/ggml-model-q4_k.gguf \
./llama-llava-cli -m MobileVLM-1.7B/ggml-model-q4_k.gguf \
--mmproj MobileVLM-1.7B/mmproj-model-f16.gguf \
--image path/to/an/image.jpg \
-p "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>\nWho is the author of this book? Answer the question using a single word or phrase. ASSISTANT:"
@ -62,7 +62,7 @@ python ./examples/convert-legacy-llama.py path/to/MobileVLM-1.7B
5. Use `quantize` to convert LLaMA part's DataType from `fp16` to `q4_k`
```sh
./quantize path/to/MobileVLM-1.7B/ggml-model-f16.gguf path/to/MobileVLM-1.7B/ggml-model-q4_k.gguf q4_k_s
./llama-quantize path/to/MobileVLM-1.7B/ggml-model-f16.gguf path/to/MobileVLM-1.7B/ggml-model-q4_k.gguf q4_k_s
```
Now both the LLaMA part and the image encoder is in the `MobileVLM-1.7B` directory.
@ -82,7 +82,7 @@ refer to `android/adb_run.sh`, modify resources' `name` and `path`
### case 1
**input**
```sh
/data/local/tmp/llava-cli \
/data/local/tmp/llama-llava-cli \
-m /data/local/tmp/ggml-model-q4_k.gguf \
--mmproj /data/local/tmp/mmproj-model-f16.gguf \
-t 4 \
@ -102,7 +102,7 @@ llama_print_timings: total time = 34731.93 ms
### case 2
**input**
```sh
/data/local/tmp/llava-cli \
/data/local/tmp/llama-llava-cli \
-m /data/local/tmp/ggml-model-q4_k.gguf \
--mmproj /data/local/tmp/mmproj-model-f16.gguf \
-t 4 \
@ -126,7 +126,7 @@ llama_print_timings: total time = 34570.79 ms
#### llava-cli release-b2005
**input**
```sh
/data/local/tmp/llava-cli \
/data/local/tmp/llama-llava-cli \
-m /data/local/tmp/ggml-model-q4_k.gguf \
--mmproj /data/local/tmp/mmproj-model-f16.gguf \
-t 4 \
@ -200,7 +200,7 @@ make LLAMA_CUDA=1 CUDA_DOCKER_ARCH=sm_87 LLAMA_CUDA_F16=1 -j 32
### case 1
**input**
```sh
./llava-cli \
./llama-llava-cli \
-m /data/local/tmp/ggml-model-q4_k.gguf \
--mmproj /data/local/tmp/mmproj-model-f16.gguf \
--image /data/local/tmp/demo.jpeg \
@ -224,7 +224,7 @@ llama_print_timings: total time = 1352.63 ms / 252 tokens
### case 2
**input**
```sh
./llava-cli \
./llama-llava-cli \
-m /data/local/tmp/ggml-model-q4_k.gguf \
--mmproj /data/local/tmp/mmproj-model-f16.gguf \
-p "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>\nWhat is in the image? ASSISTANT:" \

10
examples/llava/README.md
View File

@ -11,12 +11,12 @@ For llava-1.6 a variety of prepared gguf models are available as well [7b-34b](h
After API is confirmed, more models will be supported / uploaded.
## Usage
Build with cmake or run `make llava-cli` to build it.
Build with cmake or run `make llama-llava-cli` to build it.
After building, run: `./llava-cli` to see the usage. For example:
After building, run: `./llama-llava-cli` to see the usage. For example:
```sh
./llava-cli -m ../llava-v1.5-7b/ggml-model-f16.gguf --mmproj ../llava-v1.5-7b/mmproj-model-f16.gguf --image path/to/an/image.jpg
./llama-llava-cli -m ../llava-v1.5-7b/ggml-model-f16.gguf --mmproj ../llava-v1.5-7b/mmproj-model-f16.gguf --image path/to/an/image.jpg
```
**note**: A lower temperature like 0.1 is recommended for better quality. add `--temp 0.1` to the command to do so.
@ -95,9 +95,9 @@ python ./examples/llava/convert-image-encoder-to-gguf.py -m vit --llava-projecto
python ./examples/convert-legacy-llama.py ../llava-v1.6-vicuna-7b/ --skip-unknown
```
7) And finally we can run the llava-cli using the 1.6 model version:
7) And finally we can run the llava cli using the 1.6 model version:
```console
./llava-cli -m ../llava-v1.6-vicuna-7b/ggml-model-f16.gguf --mmproj vit/mmproj-model-f16.gguf --image some-image.jpg -c 4096
./llama-llava-cli -m ../llava-v1.6-vicuna-7b/ggml-model-f16.gguf --mmproj vit/mmproj-model-f16.gguf --image some-image.jpg -c 4096
```
**note** llava-1.6 needs more context than llava-1.5, at least 3000 is needed (just run it at -c 4096)

2
examples/llava/android/adb_run.sh
View File

@ -10,7 +10,7 @@ prompt="A chat between a curious user and an artificial intelligence assistant.
# prompt="A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>\nWhat is in the image? ASSISTANT:"
program_dir="build_64/bin"
binName="llava-cli"
binName="llama-llava-cli"
n_threads=4

2
examples/lookahead/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET lookahead)
set(TARGET llama-lookahead)
add_executable(${TARGET} lookahead.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

8
examples/lookup/CMakeLists.txt
View File

@ -1,22 +1,22 @@
set(TARGET lookup)
set(TARGET llama-lookup)
add_executable(${TARGET} lookup.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
target_compile_features(${TARGET} PRIVATE cxx_std_11)
set(TARGET lookup-create)
set(TARGET llama-lookup-create)
add_executable(${TARGET} lookup-create.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
target_compile_features(${TARGET} PRIVATE cxx_std_11)
set(TARGET lookup-merge)
set(TARGET llama-lookup-merge)
add_executable(${TARGET} lookup-merge.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
target_compile_features(${TARGET} PRIVATE cxx_std_11)
set(TARGET lookup-stats)
set(TARGET llama-lookup-stats)
add_executable(${TARGET} lookup-stats.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

8
examples/lookup/lookup-merge.cpp
View File

@ -11,14 +11,14 @@
#include <unordered_map>
#include <vector>
static void print_usage() {
static void print_usage(char* argv0) {
fprintf(stderr, "Merges multiple lookup cache files into a single one.\n");
fprintf(stderr, "Usage: lookup-merge [--help] lookup_part_1.bin lookup_part_2.bin ... lookup_merged.bin\n");
fprintf(stderr, "Usage: %s [--help] lookup_part_1.bin lookup_part_2.bin ... lookup_merged.bin\n", argv0);
}
int main(int argc, char ** argv){
if (argc < 3) {
print_usage();
print_usage(argv[0]);
exit(1);
}
@ -27,7 +27,7 @@ int main(int argc, char ** argv){
for (int i = 0; i < argc-1; ++i) {
args[i] = argv[i+1];
if (args[i] == "-h" || args[i] == "--help") {
print_usage();
print_usage(argv[0]);
exit(0);
}
}

8
examples/main-cmake-pkg/CMakeLists.txt
View File

@ -1,12 +1,12 @@
cmake_minimum_required(VERSION 3.12)
project("main-cmake-pkg" C CXX)
set(TARGET main-cmake-pkg)
project("llama-cli-cmake-pkg" C CXX)
set(TARGET llama-cli-cmake-pkg)
find_package(Llama 0.0.1 REQUIRED)
# Bake common functionality in with target. Because applications
# using the relocatable Llama package should be outside of the
# source tree, main-cmake-pkg pretends the dependencies are built-in.
# source tree, llama-cli-cmake-pkg pretends the dependencies are built-in.
set(_common_path "${CMAKE_CURRENT_LIST_DIR}/../../common")
add_library(common OBJECT)
file(GLOB _common_files
@ -15,7 +15,7 @@ file(GLOB _common_files
)
target_sources(common PRIVATE ${_common_files})
# If the common project was part of "main-cmake-pkg" the transient
# If the common project was part of "llama-cli-cmake-pkg" the transient
# defines would automatically be attached. Because the common func-
# tionality is separate, but dependent upon the defines, it must be
# explicitly extracted from the "llama" target.

4
examples/main-cmake-pkg/README.md
View File

@ -1,6 +1,6 @@
# llama.cpp/example/main-cmake-pkg
This program builds the [main](../main) application using a relocatable CMake package. It serves as an example of using the `find_package()` CMake command to conveniently include [llama.cpp](https://github.com/ggerganov/llama.cpp) in projects which live outside of the source tree.
This program builds [llama-cli](../main) using a relocatable CMake package. It serves as an example of using the `find_package()` CMake command to conveniently include [llama.cpp](https://github.com/ggerganov/llama.cpp) in projects which live outside of the source tree.
## Building
@ -20,7 +20,7 @@ cmake --build build --config Release
cmake --install build --prefix C:/LlamaCPP
```
### Build main-cmake-pkg
### Build llama-cli-cmake-pkg
```cmd

2
examples/main/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET main)
set(TARGET llama-cli)
add_executable(${TARGET} main.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

24
examples/main/README.md
View File

@ -1,4 +1,4 @@
# llama.cpp/example/main
# llama.cpp/examples/main
This example program allows you to use various LLaMA language models in an easy and efficient way. It is specifically designed to work with the [llama.cpp](https://github.com/ggerganov/llama.cpp) project, which provides a plain C/C++ implementation with optional 4-bit quantization support for faster, lower memory inference, and is optimized for desktop CPUs. This program can be used to perform various inference tasks with LLaMA models, including generating text based on user-provided prompts and chat-like interactions with reverse prompts.
@ -20,13 +20,13 @@ To get started right away, run the following command, making sure to use the cor
#### Unix-based systems (Linux, macOS, etc.):
```bash
./main -m models/7B/ggml-model.bin --prompt "Once upon a time"
./llama-cli -m models/7B/ggml-model.bin --prompt "Once upon a time"
```
#### Windows:
```powershell
main.exe -m models\7B\ggml-model.bin --prompt "Once upon a time"
llama-cli.exe -m models\7B\ggml-model.bin --prompt "Once upon a time"
```
For an interactive experience, try this command:
@ -34,7 +34,7 @@ For an interactive experience, try this command:
#### Unix-based systems (Linux, macOS, etc.):
```bash
./main -m models/7B/ggml-model.bin -n -1 --color -r "User:" --in-prefix " " -i -p \
./llama-cli -m models/7B/ggml-model.bin -n -1 --color -r "User:" --in-prefix " " -i -p \
'User: Hi
AI: Hello. I am an AI chatbot. Would you like to talk?
User: Sure!
@ -45,7 +45,7 @@ User:'
#### Windows:
```powershell
main.exe -m models\7B\ggml-model.bin -n -1 --color -r "User:" --in-prefix " " -i -e -p "User: Hi\nAI: Hello. I am an AI chatbot. Would you like to talk?\nUser: Sure!\nAI: What would you like to talk about?\nUser:"
llama-cli.exe -m models\7B\ggml-model.bin -n -1 --color -r "User:" --in-prefix " " -i -e -p "User: Hi\nAI: Hello. I am an AI chatbot. Would you like to talk?\nUser: Sure!\nAI: What would you like to talk about?\nUser:"
```
The following command generates "infinite" text from a starting prompt (you can use `Ctrl-C` to stop it):
@ -53,18 +53,18 @@ The following command generates "infinite" text from a starting prompt (you can
#### Unix-based systems (Linux, macOS, etc.):
```bash
./main -m models/7B/ggml-model.bin --ignore-eos -n -1
./llama-cli -m models/7B/ggml-model.bin --ignore-eos -n -1
```
#### Windows:
```powershell
main.exe -m models\7B\ggml-model.bin --ignore-eos -n -1
llama-cli.exe -m models\7B\ggml-model.bin --ignore-eos -n -1
```
## Common Options
In this section, we cover the most commonly used options for running the `main` program with the LLaMA models:
In this section, we cover the most commonly used options for running the `llama-cli` program with the LLaMA models:
- `-m FNAME, --model FNAME`: Specify the path to the LLaMA model file (e.g., `models/7B/ggml-model.gguf`; inferred from `--model-url` if set).
- `-mu MODEL_URL --model-url MODEL_URL`: Specify a remote http url to download the file (e.g https://huggingface.co/ggml-org/models/resolve/main/phi-2/ggml-model-q4_0.gguf).
@ -74,7 +74,7 @@ In this section, we cover the most commonly used options for running the `main`
## Input Prompts
The `main` program provides several ways to interact with the LLaMA models using input prompts:
The `llama-cli` program provides several ways to interact with the LLaMA models using input prompts:
- `--prompt PROMPT`: Provide a prompt directly as a command-line option.
- `--file FNAME`: Provide a file containing a prompt or multiple prompts.
@ -82,7 +82,7 @@ The `main` program provides several ways to interact with the LLaMA models using
## Interaction
The `main` program offers a seamless way to interact with LLaMA models, allowing users to engage in real-time conversations or provide instructions for specific tasks. The interactive mode can be triggered using various options, including `--interactive` and `--interactive-first`.
The `llama-cli` program offers a seamless way to interact with LLaMA models, allowing users to engage in real-time conversations or provide instructions for specific tasks. The interactive mode can be triggered using various options, including `--interactive` and `--interactive-first`.
In interactive mode, users can participate in text generation by injecting their input during the process. Users can press `Ctrl+C` at any time to interject and type their input, followed by pressing `Return` to submit it to the LLaMA model. To submit additional lines without finalizing input, users can end the current line with a backslash (`\`) and continue typing.
@ -107,7 +107,7 @@ To overcome this limitation, you can use the `--in-prefix` flag to add a space o
The `--in-prefix` flag is used to add a prefix to your input, primarily, this is used to insert a space after the reverse prompt. Here's an example of how to use the `--in-prefix` flag in conjunction with the `--reverse-prompt` flag:
```sh
./main -r "User:" --in-prefix " "
./llama-cli -r "User:" --in-prefix " "
```
### In-Suffix
@ -115,7 +115,7 @@ The `--in-prefix` flag is used to add a prefix to your input, primarily, this is
The `--in-suffix` flag is used to add a suffix after your input. This is useful for adding an "Assistant:" prompt after the user's input. It's added after the new-line character (`\n`) that's automatically added to the end of the user's input. Here's an example of how to use the `--in-suffix` flag in conjunction with the `--reverse-prompt` flag:
```sh
./main -r "User:" --in-prefix " " --in-suffix "Assistant:"
./llama-cli -r "User:" --in-prefix " " --in-suffix "Assistant:"
```
## Context Management

2
examples/parallel/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET parallel)
set(TARGET llama-parallel)
add_executable(${TARGET} parallel.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

2
examples/passkey/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET passkey)
set(TARGET llama-passkey)
add_executable(${TARGET} passkey.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

2
examples/passkey/README.md
View File

@ -8,5 +8,5 @@ See the following PRs for more info:
### Usage
```bash
make -j && ./passkey -m ./models/llama-7b-v2/ggml-model-f16.gguf --junk 250
make -j && ./llama-passkey -m ./models/llama-7b-v2/ggml-model-f16.gguf --junk 250
```

2
examples/perplexity/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET perplexity)
set(TARGET llama-perplexity)
add_executable(${TARGET} perplexity.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

2
examples/perplexity/perplexity.cpp
View File

@ -476,7 +476,7 @@ static results_perplexity perplexity(llama_context * ctx, const gpt_params & par
}
// Download: https://huggingface.co/datasets/ggml-org/ci/resolve/main/wikitext-2-raw-v1.zip
// Run `./perplexity -m models/7B/ggml-model-q4_0.bin -f wiki.test.raw`
// Run `./llama-perplexity -m models/7B/ggml-model-q4_0.bin -f wiki.test.raw`
// Output: `perplexity: 13.5106 [114/114]`
// BOS tokens will be added for each chunk before eval

2
examples/quantize-stats/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET quantize-stats)
set(TARGET llama-quantize-stats)
add_executable(${TARGET} quantize-stats.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE llama build_info ${CMAKE_THREAD_LIBS_INIT})

2
examples/quantize/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET quantize)
set(TARGET llama-quantize)
add_executable(${TARGET} quantize.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE llama common ${CMAKE_THREAD_LIBS_INIT})

6
examples/quantize/tests.sh
View File

@ -18,9 +18,9 @@ fi
set -x
SPLIT=$1/gguf-split
QUANTIZE=$1/quantize
MAIN=$1/main
SPLIT=$1/llama-gguf-split
QUANTIZE=$1/llama-quantize
MAIN=$1/llama-cli
WORK_PATH=$TMP_DIR/quantize
ROOT_DIR=$(realpath $(dirname $0)/../../)

2
examples/reason-act.sh
View File

@ -8,7 +8,7 @@ if [ "$1" == "-m" ]; then
MODEL="-m $2 "
fi
./main $MODEL --color \
./llama-cli $MODEL --color \
-f ./prompts/reason-act.txt \
-i --interactive-first \
--top_k 10000 --temp 0.2 --repeat_penalty 1 -t 7 -c 2048 \

2
examples/retrieval/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET retrieval)
set(TARGET llama-retrieval)
add_executable(${TARGET} retrieval.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

2
examples/retrieval/README.md
View File

@ -15,7 +15,7 @@ https://github.com/ggerganov/llama.cpp/pull/6193
`retrieval` example can be tested as follows:
```bash
make -j && ./retrieval --model ./models/bge-base-en-v1.5-f16.gguf --top-k 3 --context-file README.md --context-file License --chunk-size 100 --chunk-separator .
make -j && ./llama-retrieval --model ./models/bge-base-en-v1.5-f16.gguf --top-k 3 --context-file README.md --context-file License --chunk-size 100 --chunk-separator .
```
This chunks and embeds all given files and starts a loop requesting query inputs:

2
examples/rpc/README.md
View File

@ -70,5 +70,5 @@ cmake --build . --config Release
Finally, use the `--rpc` option to specify the host and port of each `rpc-server`:
```bash
$ bin/main -m ../models/tinyllama-1b/ggml-model-f16.gguf -p "Hello, my name is" --repeat-penalty 1.0 -n 64 --rpc 192.168.88.10:50052,192.168.88.11:50052 -ngl 99
$ bin/llama-cli -m ../models/tinyllama-1b/ggml-model-f16.gguf -p "Hello, my name is" --repeat-penalty 1.0 -n 64 --rpc 192.168.88.10:50052,192.168.88.11:50052 -ngl 99
```

2
examples/save-load-state/CMakeLists.txt
View File

@ -1,4 +1,4 @@
set(TARGET save-load-state)
set(TARGET llama-save-load-state)
add_executable(${TARGET} save-load-state.cpp)
install(TARGETS ${TARGET} RUNTIME)
target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})

2
examples/server-llama2-13B.sh
View File

@ -16,7 +16,7 @@ GEN_OPTIONS="${GEN_OPTIONS:---ctx_size 4096 --batch-size 1024}"
# shellcheck disable=SC2086 # Intended splitting of GEN_OPTIONS
./server $GEN_OPTIONS \
./llama-server $GEN_OPTIONS \
--model "$MODEL" \
--threads "$N_THREAD" \
--rope-freq-scale 1.0 \

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