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IPEX-LLM Examples
================================
You can use IPEX-LLM to run any PyTorch model with INT4 optimizations on Intel XPU (from Laptop to GPU to Cloud).
Here, we provide examples to help you quickly get started using IPEX-LLM to run some popular open-source models in the community. Please refer to the appropriate guide based on your device:
* `CPU <./examples_cpu.html>`_
* `GPU <./examples_gpu.html>`_

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# IPEX-LLM Examples: CPU
Here, we provide some examples on how you could apply IPEX-LLM INT4 optimizations on popular open-source models in the community.
To run these examples, please first refer to [here](./install_cpu.html) for more information about how to install ``ipex-llm``, requirements and best practices for setting up your environment.
The following models have been verified on either servers or laptops with Intel CPUs.
## Example of PyTorch API
| Model | Example of PyTorch API |
|------------|-------------------------------------------------------|
| LLaMA 2 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/PyTorch-Models/Model/llama2) |
| ChatGLM | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/PyTorch-Models/Model/chatglm) |
| Mistral | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/PyTorch-Models/Model/mistral) |
| Bark | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/PyTorch-Models/Model/bark) |
| BERT | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/PyTorch-Models/Model/bert) |
| Openai Whisper | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/PyTorch-Models/Model/openai-whisper) |
```eval_rst
.. important::
In addition to INT4 optimization, IPEX-LLM also provides other low bit optimizations (such as INT8, INT5, NF4, etc.). You may apply other low bit optimizations through PyTorch API as `example <https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/PyTorch-Models/More-Data-Types>`_.
```
## Example of `transformers`-style API
| Model | Example of `transformers`-style API |
|------------|-------------------------------------------------------|
| LLaMA *(such as Vicuna, Guanaco, Koala, Baize, WizardLM, etc.)* | [link1](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/Native-Models), [link2](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/vicuna) |
| LLaMA 2 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/PyTorch-Models/Model/llama2) | [link1](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/Native-Models), [link2](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/llama2) |
| ChatGLM | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/PyTorch-Models/Model/chatglm) | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/chatglm) |
| ChatGLM2 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/chatglm2) |
| Mistral | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/mistral) |
| Falcon | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/falcon) |
| MPT | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/mpt) |
| Dolly-v1 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/dolly_v1) |
| Dolly-v2 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/dolly_v2) |
| Replit Code| [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/replit) |
| RedPajama | [link1](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/Native-Models), [link2](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/redpajama) |
| Phoenix | [link1](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/Native-Models), [link2](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/phoenix) |
| StarCoder | [link1](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/Native-Models), [link2](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/starcoder) |
| Baichuan | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/baichuan) |
| Baichuan2 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/baichuan2) |
| InternLM | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/internlm) |
| Qwen | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/qwen) |
| Aquila | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/aquila) |
| MOSS | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/moss) |
| Whisper | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/whisper) |
```eval_rst
.. important::
In addition to INT4 optimization, IPEX-LLM also provides other low bit optimizations (such as INT8, INT5, NF4, etc.). You may apply other low bit optimizations through ``transformers``-style API as `example <https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/More-Data-Types>`_.
```
```eval_rst
.. seealso::
See the complete examples `here <https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU>`_.
```

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# IPEX-LLM Examples: GPU
Here, we provide some examples on how you could apply IPEX-LLM INT4 optimizations on popular open-source models in the community.
To run these examples, please first refer to [here](./install_gpu.html) for more information about how to install ``ipex-llm``, requirements and best practices for setting up your environment.
```eval_rst
.. important::
Only Linux system is supported now, Ubuntu 22.04 is prefered.
```
The following models have been verified on either servers or laptops with Intel GPUs.
## Example of PyTorch API
| Model | Example of PyTorch API |
|------------|-------------------------------------------------------|
| LLaMA 2 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/PyTorch-Models/Model/llama2) |
| ChatGLM 2 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/PyTorch-Models/Model/chatglm2) |
| Mistral | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/PyTorch-Models/Model/mistral) |
| Baichuan | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/PyTorch-Models/Model/baichuan) |
| Baichuan2 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/PyTorch-Models/Model/baichuan2) |
| Replit | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/PyTorch-Models/Model/replit) |
| StarCoder | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/PyTorch-Models/Model/starcoder) |
| Dolly-v1 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/PyTorch-Models/Model/dolly-v1) |
| Dolly-v2 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/PyTorch-Models/Model/dolly-v2) |
```eval_rst
.. important::
In addition to INT4 optimization, IPEX-LLM also provides other low bit optimizations (such as INT8, INT5, NF4, etc.). You may apply other low bit optimizations through PyTorch API as `example <https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/PyTorch-Models/More-Data-Types>`_.
```
## Example of `transformers`-style API
| Model | Example of `transformers`-style API |
|------------|-------------------------------------------------------|
| LLaMA *(such as Vicuna, Guanaco, Koala, Baize, WizardLM, etc.)* |[link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Model/vicuna)|
| LLaMA 2 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Model/llama2) |
| ChatGLM2 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Model/chatglm2) |
| Mistral | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Model/mistral) |
| Falcon | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Model/falcon) |
| MPT | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/mpt) |
| Dolly-v1 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/dolly_v1) |
| Dolly-v2 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/dolly_v2) |
| Replit | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/replit) |
| StarCoder | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Model/starcoder) |
| Baichuan | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/baichuan) |
| Baichuan2 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Model/baichuan2) |
| InternLM | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Model/internlm) |
| Qwen | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Model/qwen) |
| Aquila | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Model/aquila) |
| Whisper | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Model/whisper) |
| Chinese Llama2 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Model/chinese-llama2) |
| GPT-J | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Model/gpt-j) |
```eval_rst
.. important::
In addition to INT4 optimization, IPEX-LLM also provides other low bit optimizations (such as INT8, INT5, NF4, etc.). You may apply other low bit optimizations through ``transformers``-style API as `example <https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/More-Data-Types>`_.
```
```eval_rst
.. seealso::
See the complete examples `here <https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU>`_.
```