* add Qwen1.5-7B-Chat * modify Qwen1.5 example * update README * update prompt format * update folder name and example README * add Chinese prompt sample output * update link in README * correct the link * update transformer version
		
			
				
	
	
	
	
		
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	Qwen1.5
In this directory, you will find examples on how you could apply BigDL-LLM INT4 optimizations on Qwen1.5 models on Intel GPUs. For illustration purposes, we utilize the Qwen/Qwen1.5-7B-Chat as a reference InternLM 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 Qwen1.5 model to predict the next N tokens using generate() API, with BigDL-LLM INT4 optimizations on Intel GPUs.
1. Install
1.1 Installation on Linux
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
pip install transformers==4.37.0 # install transformers which supports Qwen2
1.2 Installation on Windows
We suggest using conda to manage environment:
conda create -n llm python=3.9 libuv
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
pip install transformers==4.37.2 # install transformers which supports Qwen2
2. Configures OneAPI environment variables
2.1 Configurations for Linux
source /opt/intel/oneapi/setvars.sh
2.2 Configurations for Windows
call "C:\Program Files (x86)\Intel\oneAPI\setvars.bat"
Note: Please make sure you are using CMD (Anaconda Prompt if using conda) to run the command as PowerShell is not supported.
3. Runtime Configurations
For optimal performance, it is recommended to set several environment variables. Please check out the suggestions based on your device.
3.1 Configurations for Linux
For Intel Arc™ A-Series Graphics and Intel Data Center GPU Flex Series
export USE_XETLA=OFF
export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
For Intel Data Center GPU Max Series
export LD_PRELOAD=${LD_PRELOAD}:${CONDA_PREFIX}/lib/libtcmalloc.so
export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
export ENABLE_SDP_FUSION=1
Note: Please note that
libtcmalloc.socan be installed byconda install -c conda-forge -y gperftools=2.10.
3.2 Configurations for Windows
For Intel iGPU
set SYCL_CACHE_PERSISTENT=1
set BIGDL_LLM_XMX_DISABLED=1
For Intel Arc™ A300-Series or Pro A60
set SYCL_CACHE_PERSISTENT=1
For other Intel dGPU Series
There is no need to set further environment variables.
Note: For the first time that each model runs on Intel iGPU/Intel Arc™ A300-Series or Pro A60, it may take several minutes to compile.
4. Running examples
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 Qwen1.5 model (e.g.Qwen/Qwen1.5-7B-Chat) to be downloaded, or the path to the huggingface checkpoint folder. It is default to be'Qwen/Qwen1.5-7B-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 be32.
Sample Output
Qwen/Qwen1.5-7B-Chat
Inference time: xxxx s
-------------------- Prompt --------------------
<|im_start|>system
You are a helpful assistant.<|im_end|>
<|im_start|>user
AI是什么?<|im_end|>
<|im_start|>assistant
-------------------- Output --------------------
<|im_start|>system
You are a helpful assistant.<|im_end|>
<|im_start|>user
AI是什么?<|im_end|>
<|im_start|>assistant
人工智能(AI)是指通过计算机模拟、延伸和扩展人类智能的学科,其目标是使机器具有学习、推理、感知、理解、交流
Inference time: xxxx s
-------------------- Prompt --------------------
<|im_start|>system
You are a helpful assistant.<|im_end|>
<|im_start|>user
What is AI?<|im_end|>
<|im_start|>assistant
-------------------- Output --------------------
<|im_start|>system
You are a helpful assistant.<|im_end|>
<|im_start|>user
What is AI?<|im_end|>
<|im_start|>assistant
AI, or artificial intelligence, refers to the simulation of human intelligence in machines that are programmed to perform tasks that typically require human cognition, such as learning, reasoning