Skip to content

Latest commit

 

History

History
 
 

aquila

Folders and files

NameName
Last commit message
Last commit date

parent directory

..
README.md
README.md
 
 
generate.py
generate.py
 
 

README.md

Aquila

In this directory, you will find examples on how you could apply BigDL-LLM INT4 optimizations on Aquila models. For illustration purposes, we utilize the BAAI/AquilaChat-7B as a reference Aquila model.

Note: If you want to download the Hugging Face Transformers model, please refer to here.

BigDL-LLM optimizes the Transformers model in INT4 precision at runtime, and thus no explicit conversion is needed.

Requirements

To run these examples with BigDL-LLM, 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 Aquila model to predict the next N tokens using generate() API, with BigDL-LLM INT4 optimizations.

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==2.0.110+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

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 In the example, several arguments can be passed to satisfy your requirements:

  • --repo-id-or-model-path: str, argument defining the huggingface repo id for the Aquila model to be downloaded, or the path to the huggingface checkpoint folder. It is default to be 'BAAI/AquilaChat-7B'.
  • --prompt: str, argument defining the prompt to be inferred (with integrated prompt format for chat). It is default to be 'AI是什么？'.
  • --n-predict: int, argument defining the max number of tokens to predict. It is default to be 32.

Sample Output

BAAI/AquilaChat-7B

Inference time: xxxx s
-------------------- Prompt --------------------
Human: AI是什么？###Assistant:
-------------------- Output --------------------
Human: AI是什么？###Assistant: AI是人工智能的缩写。人工智能是一种技术，旨在使计算机能够像人类一样思考、学习和执行任务。AI包括许多不同的技术和方法，例如机器