Inference Llama 2 in one file of pure Python
Project description
llama2.py
why this fork?
This repository serves as a fork that provides a Python-based implementation of llama2.c
. Designed for an extensive audience, it aims to be a straightforward "reference implementation" suitable for educational purposes.
The current llama2.c
repository comprises two Python files intended for model training and one C file for inference. Our goal is to bridge the existing gap by offering a clear-cut reference implementation encapsulating all transformer logic within a concise Python file, not exceeding 500 lines of code.
Though the original Facebook/llama is written on Python, its complexity is rather high due to multiple dependencies and sophisticated optimizations implemented within. This often makes it hard to follow, particularly for those new to the field.
Please note, the current performance of our implementation is relatively slow, clocking in at approximately ~1 tok/sec
. This leaves ample scope for significant performance optimizations. We welcome any contributions towards enhancing the efficiency of this project.
feel the magic
First, navigate to the folder when you keep your projects and clone this repository to this folder:
git clone https://github.com/tairov/llama2.py.git
Then, open the repository folder:
cd llama2.py
Now, let's just run a baby Llama 2 model in Python
wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories15M.bin
Just run the Python
python3 llama2.py stories15M.bin 0.8 256 "Dream comes true this day"
<s>
Dream comes true this day. To their surprise. A big game was easy and everyone was going on the day. Jack and they were playing beneath: life, free, butter! There was the time to think of the universe. There was very happy, fun and the joy and the following down below of this day they were there was a lot of a wide, new camping.
Jack and they had happened. The town was the saving up above the camp of the waves shor of their laughter, friendly journey of friendship to one. The night sky show of the end. Little ceremony, happy again.
<s>
Once upon his family of a big day when Jack. They were filled foreshadowed happy and they were the joy filled this, different: the King of their appreciation they were to a wave to the spring limit. They were becoming Ruby, happy and the sunset of life of an amazing friendship and he had a robot.
<s>
Once upon a 4, happy to the wonderful experience of the celebration of their friendship. Even the playground.
Jack and Sammy fishing adventure foreshium of a wishing being free time, happy. The generous adventure foreshly made it. The chance to
achieved tok/s: 1.3463711338028914
performance
Performance is awful at the moment.
On my Mac M1 Max -- ~1.3 tok / sec
License
MIT
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for llama2_py-0.0.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 4ec88926c855209d21b4d88a44c667698a5f14cd5af939b21ae9c878ad40160b |
|
MD5 | 174fda4d3c66bd1ef2b4b7b9abd219ef |
|
BLAKE2b-256 | 0fc371379debb591c03f688ba1e9e1d3c0a536efd086c6d24fc00597f59a543b |