mirror of
https://github.com/ggerganov/llama.cpp.git
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1c641e6aac
* `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
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.. | ||
CMakeLists.txt | ||
quantize.cpp | ||
README.md | ||
tests.sh |
quantize
You can also use the GGUF-my-repo space on Hugging Face to build your own quants without any setup.
Note: It is synced from llama.cpp main
every 6 hours.
Llama 2 7B
Quantization | Bits per Weight (BPW) |
---|---|
Q2_K | 3.35 |
Q3_K_S | 3.50 |
Q3_K_M | 3.91 |
Q3_K_L | 4.27 |
Q4_K_S | 4.58 |
Q4_K_M | 4.84 |
Q5_K_S | 5.52 |
Q5_K_M | 5.68 |
Q6_K | 6.56 |
Llama 2 13B
Quantization | Bits per Weight (BPW) |
---|---|
Q2_K | 3.34 |
Q3_K_S | 3.48 |
Q3_K_M | 3.89 |
Q3_K_L | 4.26 |
Q4_K_S | 4.56 |
Q4_K_M | 4.83 |
Q5_K_S | 5.51 |
Q5_K_M | 5.67 |
Q6_K | 6.56 |
Llama 2 70B
Quantization | Bits per Weight (BPW) |
---|---|
Q2_K | 3.40 |
Q3_K_S | 3.47 |
Q3_K_M | 3.85 |
Q3_K_L | 4.19 |
Q4_K_S | 4.53 |
Q4_K_M | 4.80 |
Q5_K_S | 5.50 |
Q5_K_M | 5.65 |
Q6_K | 6.56 |