* Add cpu int4 example for BlueLM * addexample optimize_model cpu for bluelm * add example gpu int4 blueLM * add example optimiza_model GPU for bluelm * Fixing naming issues and BigDL package version. * Fixing naming issues... * Add BlueLM in README.md "Verified Models" |
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| .. | ||
| aquila2 | ||
| baichuan | ||
| baichuan2 | ||
| bluelm | ||
| chatglm2 | ||
| chatglm3 | ||
| codellama | ||
| distil-whisper | ||
| dolly-v1 | ||
| dolly-v2 | ||
| flan-t5 | ||
| llama2 | ||
| llava | ||
| mistral | ||
| phi-1_5 | ||
| qwen-vl | ||
| replit | ||
| starcoder | ||
| yi | ||
| README.md | ||
BigDL-LLM INT4 Optimization for Large Language Model on Intel GPUs
You can use optimize_model API to accelerate general PyTorch models on Intel GPUs. 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 Hardware Platforms
- Intel Arc™ A-Series Graphics
- Intel Data Center GPU Flex Series
- Intel Data Center GPU Max Series
Recommended Requirements
To apply Intel GPU acceleration, there’re several steps for tools installation and environment preparation.
Step 1, only Linux system is supported now, Ubuntu 22.04 is prefered.
Step 2, please refer to our driver installation for general purpose GPU capabilities.
Note
: IPEX 2.0.110+xpu requires Intel GPU Driver version is Stable 647.21.
Step 3, you also need to download and install Intel® oneAPI Base Toolkit. OneMKL and DPC++ compiler are needed, others are optional.
Note
: IPEX 2.0.110+xpu requires Intel® oneAPI Base Toolkit's version >= 2023.2.0.
Best Known Configuration on Linux
For better performance, it is recommended to set environment variables on Linux:
export USE_XETLA=OFF
export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1