* Set BIGDL_IMPORT_IPEX default to true, i.e., auto import IPEX for XPU. * Remove import intel_extension_for_pytorch as ipex from GPU example. * Add support for bigdl-core-xe-21. |
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| generate.py | ||
| README.md | ||
Mistral
In this directory, you will find examples on how you could apply BigDL-LLM INT4 optimizations on Mistral models on Intel GPUs. For illustration purposes, we utilize the mistralai/Mistral-7B-Instruct-v0.1 and mistralai/Mistral-7B-v0.1 as reference Mistral models.
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.
Important: According to Mistral Troubleshooting, please make sure you have installed transformers==4.34.0 to run the example.
Example: Predict Tokens using generate() API
In the example generate.py, we show a basic use case for a Mistral 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 the Python environment. For more information about conda installation, please refer to here.
After installing conda, create a Python environment for BigDL-LLM:
conda create -n llm python=3.9 # recommend to use Python 3.9
conda activate llm
# below command will install intel_extension_for_pytorch==2.0.110+xpu as default
# you can install specific ipex/torch version for your need
pip install --pre --upgrade bigdl-llm[xpu] -f https://developer.intel.com/ipex-whl-stable-xpu
# Refer to https://huggingface.co/mistralai/Mistral-7B-v0.1#troubleshooting, please make sure you are using a stable version of Transformers, 4.34.0 or newer.
pip install transformers==4.34.0
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 --prompt 'What is AI?'
In the example, several arguments can be passed to satisfy your requirements:
--repo-id-or-model-path REPO_ID_OR_MODEL_PATH: argument defining the huggingface repo id for the Mistral model (e.g.mistralai/Mistral-7B-Instruct-v0.1andmistralai/Mistral-7B-v0.1) to be downloaded, or the path to the huggingface checkpoint folder. It is default to be'mistralai/Mistral-7B-Instruct-v0.1'.--prompt PROMPT: argument defining the prompt to be infered (with integrated prompt format for chat). It is default to be'What is AI?'.--n-predict N_PREDICT: argument defining the max number of tokens to predict. It is default to be32.
2.3 Sample Output
mistralai/Mistral-7B-Instruct-v0.1
Inference time: xxxx s
-------------------- Output --------------------
[INST] What is AI? [/INST] AI stands for Artificial Intelligence. It is a branch of computer science that focuses on the development of intelligent machines that work, react, and even think like humans
mistralai/Mistral-7B-v0.1
Inference time: xxxx s
-------------------- Output --------------------
[INST] What is AI? [/INST]
[INST] Artificial Intelligence (AI) is a branch of computer science that deals with the simulation of intelligent behavior in computers. It is a broad