ipex-llm/python/llm/example/GPU
yb-peng a2c1675546 Add CPU and GPU examples for Yuan2-2B-hf (#9946)
* Add a new CPU example of Yuan2-2B-hf

* Add a new CPU generate.py of Yuan2-2B-hf example

* Add a new GPU example of Yuan2-2B-hf

* Add Yuan2 to README table

* In CPU example:1.Use English as default prompt; 2.Provide modified files in yuan2-2B-instruct

* In GPU example:1.Use English as default prompt;2.Provide modified files

* GPU example:update README

* update Yuan2-2B-hf in README table

* Add CPU example for Yuan2-2B in Pytorch-Models

* Add GPU example for Yuan2-2B in Pytorch-Models

* Add license in generate.py; Modify README

* In GPU Add license in generate.py; Modify README

* In CPU yuan2 modify README

* In GPU yuan2 modify README

* In CPU yuan2 modify README

* In GPU example, updated the readme for Windows GPU supports

* In GPU torch example, updated the readme for Windows GPU supports

* GPU hf example README modified

* GPU example README modified
2024-02-23 14:09:30 +08:00
..
Applications/autogen Add AutoGen CPU and XPU Example (#9980) 2024-01-31 11:31:18 +08:00
Deepspeed-AutoTP LLM: add avg token latency information and benchmark guide of autotp (#9940) 2024-01-19 15:09:57 +08:00
HF-Transformers-AutoModels Add CPU and GPU examples for Yuan2-2B-hf (#9946) 2024-02-23 14:09:30 +08:00
LLM-Finetuning LLM: add qlora finetuning example using trl.SFTTrainer (#10183) 2024-02-21 16:40:04 +08:00
ModelScope-Models LLM: add Modelscope model example (#10126) 2024-02-08 11:18:07 +08:00
PyTorch-Models Add CPU and GPU examples for Yuan2-2B-hf (#9946) 2024-02-23 14:09:30 +08:00
Speculative-Decoding LLM: Support gpt-j in speculative decoding (#10067) 2024-02-02 14:54:55 +08:00
vLLM-Serving Update llm gpu xpu default related info to PyTorch 2.1 (#9866) 2024-01-09 15:38:47 +08:00
README.md LLM: add Modelscope model example (#10126) 2024-02-08 11:18:07 +08:00

BigDL-LLM Examples on Intel GPU

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

  • Applications: running LLM applications (such as autogen) on BigDL-LLM
  • HF-Transformers-AutoModels: running any Hugging Face Transformers model on BigDL-LLM (using the standard AutoModel APIs)
  • LLM-Finetuning: running finetuning (such as LoRA, QLoRA, QA-LoRA, etc) 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")
  • Speculative-Decoding: running any Hugging Face Transformers model with self-speculative decoding on Intel GPUs
  • ModelScope-Models: running ModelScope model with BigDL-LLM on Intel GPUs

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, therere several steps for tools installation and environment preparation. See the GPU installation guide for mode details.