ipex-llm/python/llm/example/CPU/HF-Transformers-AutoModels/Model
2023-11-06 15:47:39 +08:00
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aquila
aquila2 LLM: add aquila2 model example (#9356) 2023-11-06 15:47:39 +08:00
baichuan
baichuan2
chatglm
chatglm2
chatglm3 LLM: add chatglm3 examples (#9305) 2023-11-01 09:50:05 +08:00
codellama LLM: add CodeLlama CPU and GPU examples (#9338) 2023-11-02 15:34:25 +08:00
codeshell add CodeShell CPU example (#9345) 2023-11-03 13:15:54 +08:00
dolly_v1
dolly_v2
falcon
flan-t5
internlm
internlm-xcomposer Add internlm_xcomposer cpu examples (#9337) 2023-11-02 15:50:02 +08:00
llama2
mistral
moss
mpt
phi-1_5
phoenix
qwen
qwen-vl use coco image in Qwen-VL (#9298) 2023-10-30 14:32:35 +08:00
redpajama
replit LLM: Add Replit CPU and GPU example (#9028) 2023-10-12 13:42:14 +08:00
skywork Add cpu examples of skywork (#9340) 2023-11-02 15:10:45 +08:00
starcoder
vicuna
whisper
wizardcoder-python Add cpu examples of WizardCoder (#9344) 2023-11-02 20:22:43 +08:00
README.md LLM: add chatglm3 examples (#9305) 2023-11-01 09:50:05 +08:00

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.

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