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* Update README in LLM GPU Examples * Update reference of Intel GPU * add cpu_embedding=True in comment * small fixes * update GPU/README.md and add explanation for cpu_embedding=True * address comments * fix small typos * add backtick for cpu_embedding=True * remove extra backtick in the doc * add period mark * update readme
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BigDL-LLM Examples on Intel GPU
This folder contains examples of running BigDL-LLM on Intel GPU:
- HF-Transformers-AutoModels: running any Hugging Face Transformers model on BigDL-LLM (using the standard AutoModel APIs)
- QLoRA-FineTuning: running QLoRA finetuning using BigDL-LLM on Intel GPUs
- vLLM-Serving: running vLLM serving framework on intel GPUs (with BigDL-LLM low-bit optimized models)
- Deepspeed-AutoTP: running distributed inference using DeepSpeed AutoTP (with BigDL-LLM low-bit optimized models) on Intel GPUs
- PyTorch-Models: running any PyTorch model on BigDL-LLM (with "one-line code change")
System Support
1. Linux:
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)
2. Windows
Hardware:
- Intel iGPU and dGPU
Operating System:
- Windows 10/11, with or without WSL
Requirements
To apply Intel GPU acceleration, there’re several steps for tools installation and environment preparation. See the GPU installation guide for mode details.