ipex-llm/python/llm/example/GPU/README.md
2023-10-09 15:36:39 +08:00

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# BigDL-LLM Examples on Intel GPU
This folder contains examples of running BigDL-LLM on Intel GPU:
- [HF-Transformers-AutoModels](HF-Transformers-AutoModels): running any Hugging Face Transformers model on BigDL-LLM (using the standard AutoModel APIs)
- [PyTorch-Models](PyTorch-Models): running any PyTorch model on BigDL-LLM (with "one-line code change")
- [QLoRA-FineTuning](QLoRA-FineTuning): running QLoRA finetuning on BigDL-LLM
## System Support
**Hardware**:
- Intel Arc™ A-Series Graphics
- Intel Data Center GPU Flex Series
- Intel Data Center GPU Max Series
**Operating System**:
- Ubuntu 20.04 or later (Ubuntu 22.04 is preferred)
## Requirements
To apply Intel GPU acceleration, therere several steps for tools installation and environment preparation.
Step 1, please refer to our [driver installation](https://dgpu-docs.intel.com/driver/installation.html) for general purpose GPU capabilities.
> **Note**: IPEX 2.0.110+xpu requires Intel GPU Driver version is [Stable 647.21](https://dgpu-docs.intel.com/releases/stable_647_21_20230714.html).
Step 2, you also need to download and install [Intel® oneAPI Base Toolkit](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit-download.html). 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.