ipex-llm/python/llm/example/GPU
Yang Wang 51d07a9fd8 Support directly loading gptq models from huggingface (#9391)
* Support directly loading GPTQ models from huggingface

* fix style

* fix tests

* change example structure

* address comments

* fix style

* address comments
2023-11-13 20:48:12 -08:00
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Deepspeed-AutoTP Add deepspeed autotp example readme (#9289) 2023-10-27 13:04:38 -07:00
HF-Transformers-AutoModels Support directly loading gptq models from huggingface (#9391) 2023-11-13 20:48:12 -08:00
PyTorch-Models Add examples for Yi-6B (#9421) 2023-11-13 10:53:15 +08:00
QLoRA-FineTuning LLM: add alpaca qlora finetuning example (#9276) 2023-11-08 16:25:17 +08:00
README.md LLM: update example layout (#9046) 2023-10-09 15:36:39 +08:00

BigDL-LLM Examples on Intel GPU

This folder contains examples of running BigDL-LLM on Intel GPU:

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 for general purpose GPU capabilities.

Note

: IPEX 2.0.110+xpu requires Intel GPU Driver version is Stable 647.21.

Step 2, 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.