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models | ||
.gitignore | ||
convert-pth-to-ggml.py | ||
ggml.c | ||
ggml.h | ||
main.cpp | ||
Makefile | ||
quantize.cpp | ||
README.md | ||
utils.cpp | ||
utils.h |
llama.cpp
Inference of Facebook's LLaMA model in pure C/C++
TEMPORARY NOTICE:
If you observe garbage results, make sure to update to latest master. There was a bug and it was fixed here: 70bc0b8b15
Description
The main goal is to run the model using 4-bit quantization on a MacBook.
- Plain C/C++ implementation without dependencies
- Apple silicon first-class citizen - optimized via Arm Neon and Accelerate framework
- Mixed F16 / F32 precision
- 4-bit quantization support
- Runs on the CPU
This was hacked in an evening - I have no idea if it works correctly.
So far, I've tested just the 7B model. Here is a "typical" run:
make -j && ./main -m ../LLaMA-4bit/7B/ggml-model-q4_0.bin -p "Building a website can be done in 10 simple steps:" -t 8 -n 512
I llama.cpp build info:
I UNAME_S: Darwin
I UNAME_P: arm
I UNAME_M: arm64
I CFLAGS: -I. -O3 -DNDEBUG -std=c11 -fPIC -pthread -DGGML_USE_ACCELERATE
I CXXFLAGS: -I. -I./examples -O3 -DNDEBUG -std=c++11 -fPIC -pthread
I LDFLAGS: -framework Accelerate
I CC: Apple clang version 14.0.0 (clang-1400.0.29.202)
I CXX: Apple clang version 14.0.0 (clang-1400.0.29.202)
make: Nothing to be done for `default'.
main: seed = 1678486056
llama_model_load: loading model from '../LLaMA-4bit/7B/ggml-model-q4_0.bin' - please wait ...
llama_model_load: n_vocab = 32000
llama_model_load: n_ctx = 512
llama_model_load: n_embd = 4096
llama_model_load: n_mult = 256
llama_model_load: n_head = 32
llama_model_load: n_layer = 32
llama_model_load: n_rot = 128
llama_model_load: f16 = 2
llama_model_load: n_ff = 11008
llama_model_load: ggml ctx size = 4529.34 MB
llama_model_load: memory_size = 512.00 MB, n_mem = 16384
llama_model_load: .................................... done
llama_model_load: model size = 4017.27 MB / num tensors = 291
main: prompt: 'Building a website can be done in 10 simple steps:'
main: number of tokens in prompt = 15
1 -> ''
8893 -> 'Build'
292 -> 'ing'
263 -> ' a'
4700 -> ' website'
508 -> ' can'
367 -> ' be'
2309 -> ' done'
297 -> ' in'
29871 -> ' '
29896 -> '1'
29900 -> '0'
2560 -> ' simple'
6576 -> ' steps'
29901 -> ':'
sampling parameters: temp = 0.800000, top_k = 40, top_p = 0.950000
Building a website can be done in 10 simple steps:
1) Select a domain name and web hosting plan
2) Complete a sitemap
3) List your products
4) Write product descriptions
5) Create a user account
6) Build the template
7) Start building the website
8) Advertise the website
9) Provide email support
10) Submit the website to search engines
A website is a collection of web pages that are formatted with HTML. HTML is the code that defines what the website looks like and how it behaves.
The HTML code is formatted into a template or a format. Once this is done, it is displayed on the user's browser.
The web pages are stored in a web server. The web server is also called a host. When the website is accessed, it is retrieved from the server and displayed on the user's computer.
A website is known as a website when it is hosted. This means that it is displayed on a host. The host is usually a web server.
A website can be displayed on different browsers. The browsers are basically the software that renders the website on the user's screen.
A website can also be viewed on different devices such as desktops, tablets and smartphones.
Hence, to have a website displayed on a browser, the website must be hosted.
A domain name is an address of a website. It is the name of the website.
The website is known as a website when it is hosted. This means that it is displayed on a host. The host is usually a web server.
A website can be displayed on different browsers. The browsers are basically the software that renders the website on the user’s screen.
A website can also be viewed on different devices such as desktops, tablets and smartphones. Hence, to have a website displayed on a browser, the website must be hosted.
A domain name is an address of a website. It is the name of the website.
A website is an address of a website. It is a collection of web pages that are formatted with HTML. HTML is the code that defines what the website looks like and how it behaves.
The HTML code is formatted into a template or a format. Once this is done, it is displayed on the user’s browser.
A website is known as a website when it is hosted
main: mem per token = 14434244 bytes
main: load time = 1332.48 ms
main: sample time = 1081.40 ms
main: predict time = 31378.77 ms / 61.41 ms per token
main: total time = 34036.74 ms
Usage
# build this repo
git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp
make
# obtain the original LLaMA model weights and place them in ./models
ls ./models
65B 30B 13B 7B tokenizer_checklist.chk tokenizer.model
# convert the 7B model to ggml FP16 format
python3 convert-pth-to-ggml.py models/7B/ 1
# quantize the model to 4-bits
./quantize ./models/7B/ggml-model-f16.bin ./models/7B/ggml-model-q4_0.bin 2
# run the inference
./main -m ./models/7B/ggml-model-q4_0.bin -t 8 -n 128
Limitations
- Currently, only LLaMA-7B is supported since I haven't figured out how to merge the tensors of the bigger models. However, in theory, you should be able to run 65B on a 64GB MacBook
- Not sure if my tokenizer is correct. There are a few places where we might have a mistake:
26c0846629/convert-pth-to-ggml.py (L79-L87)
26c0846629/utils.h (L65-L69)
In general, it seems to work, but I think it fails for unicode character support. Hopefully, someone can help with that
- I don't know yet how much the quantization affects the quality of the generated text
- Probably the token sampling can be improved
- x86 quantization support not yet ready. Basically, you want to run this on Apple Silicon