ipex-llm/python/llm/example/GPU/HF-Transformers-AutoModels/Model/bluelm
Mingyu Wei bc9cff51a8 LLM GPU Example Update for Windows Support (#9902)
* Update README in LLM GPU Examples

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* add cpu_embedding=True in comment

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* update GPU/README.md and add explanation for cpu_embedding=True

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2024-01-24 13:42:27 +08:00
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README.md LLM GPU Example Update for Windows Support (#9902) 2024-01-24 13:42:27 +08:00

BlueLM

In this directory, you will find examples on how you could apply BigDL-LLM INT4 optimizations on BlueLM models on Intel GPUs. For illustration purposes, we utilize the vivo-ai/BlueLM-7B-Chat as a reference BlueLM model.

0. Requirements

To run these examples with BigDL-LLM on Intel GPUs, we have some recommended requirements for your machine, please refer to here for more information.

Example: Predict Tokens using generate() API

In the example generate.py, we show a basic use case for a BlueLM model to predict the next N tokens using generate() API, with BigDL-LLM INT4 optimizations on Intel GPUs.

1. Install

We suggest using conda to manage environment:

conda create -n llm python=3.9
conda activate llm
# below command will install intel_extension_for_pytorch==2.1.10+xpu as default
pip install --pre --upgrade bigdl-llm[xpu] -f https://developer.intel.com/ipex-whl-stable-xpu

2. Configures OneAPI environment variables

source /opt/intel/oneapi/setvars.sh

3. Run

For optimal performance on Arc, it is recommended to set several environment variables.

export USE_XETLA=OFF
export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
python ./generate.py --repo-id-or-model-path REPO_ID_OR_MODEL_PATH --prompt PROMPT --n-predict N_PREDICT

Arguments info:

  • --repo-id-or-model-path REPO_ID_OR_MODEL_PATH: argument defining the huggingface repo id for the BlueLM model (e.g vivo-ai/BlueLM-7B-Chat) to be downloaded, or the path to the huggingface checkpoint folder. It is default to be 'vivo-ai/BlueLM-7B-Chat'.
  • --prompt PROMPT: argument defining the prompt to be infered (with integrated prompt format for chat). It is default to be 'AI是什么'.
  • --n-predict N_PREDICT: argument defining the max number of tokens to predict. It is default to be 32.

Sample Output

vivo-ai/BlueLM-7B-Chat

Inference time: xxxx s
-------------------- Prompt --------------------
[|Human|]:AI是什么[|AI|]:
-------------------- Output --------------------
AI是什么 AI是人工智能Artificial Intelligence的缩写是一种模拟人类智能思维过程的技术。它可以让计算机系统通过学习和适应自主地完成各种任务
Inference time: xxxx s
-------------------- Prompt --------------------
[|Human|]:What is AI?[|AI|]:
-------------------- Output --------------------
What is AI? AI is an AI, or artificial intelligence, that can be defined as the simulation of human intelligence processes by machines, especially computer systems.

AI is not