ipex-llm/python/llm/example/transformers/transformers_int4
Yina Chen 74a2c2ddf5 Update optimize_model=True in llama2 chatglm2 arc examples (#8878)
* add optimize_model=True in llama2 chatglm2 examples

* add ipex optimize in gpt-j example
2023-09-05 10:35:37 +08:00
..
baichuan
chatglm
chatglm2
dolly_v1
dolly_v2
falcon
GPU
internlm
llama2
moss
mpt
phoenix
qwen
redpajama
starcoder [LLM] Add more transformers int4 example (starcoder) (#8540) 2023-07-17 14:41:19 +08:00
vicuna
whisper
README.md

BigDL-LLM Transformers INT4 Optimization for Large Language Model

You can use BigDL-LLM to run any Huggingface Transformer models with INT4 optimizations on either servers or laptops. This directory contains example scripts to help you quickly get started using BigDL-LLM to run some popular open-source models in the community. Each model has its own dedicated folder, where you can find detailed instructions on how to install and run it.

Verified models

Model Example
LLaMA link
LLaMA 2 link
MPT link
Falcon link
ChatGLM link
ChatGLM2 link
MOSS link
Baichuan link
Dolly-v1 link
Dolly-v2 link
RedPajama link
Phoenix link
StarCoder link
InternLM link
Whisper link
Qwen link

To run the examples, we recommend using Intel® Xeon® processors (server), or >= 12th Gen Intel® Core™ processor (client).

For OS, BigDL-LLM supports Ubuntu 20.04 or later, CentOS 7 or later, and Windows 10/11.

Best Known Configuration on Linux

For better performance, it is recommended to set environment variables on Linux with the help of BigDL-Nano:

pip install bigdl-nano
source bigdl-nano-init