64 lines
6 KiB
Markdown
64 lines
6 KiB
Markdown
# IPEX-LLM Examples: CPU
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Here, we provide some examples on how you could apply IPEX-LLM INT4 optimizations on popular open-source models in the community.
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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.
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The following models have been verified on either servers or laptops with Intel CPUs.
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## Example of PyTorch API
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| Model | Example of PyTorch API |
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|------------|-------------------------------------------------------|
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| LLaMA 2 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/PyTorch-Models/Model/llama2) |
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| ChatGLM | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/PyTorch-Models/Model/chatglm) |
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| Mistral | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/PyTorch-Models/Model/mistral) |
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| Bark | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/PyTorch-Models/Model/bark) |
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| BERT | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/PyTorch-Models/Model/bert) |
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| Openai Whisper | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/PyTorch-Models/Model/openai-whisper) |
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```eval_rst
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.. important::
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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>`_.
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```
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## Example of `transformers`-style API
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| Model | Example of `transformers`-style API |
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|------------|-------------------------------------------------------|
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| 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) |
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| 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) |
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| 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) |
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| ChatGLM2 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/chatglm2) |
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| Mistral | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/mistral) |
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| Falcon | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/falcon) |
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| MPT | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/mpt) |
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| Dolly-v1 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/dolly_v1) |
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| Dolly-v2 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/dolly_v2) |
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| Replit Code| [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/replit) |
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| 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) |
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| 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) |
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| 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) |
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| Baichuan | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/baichuan) |
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| Baichuan2 | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/baichuan2) |
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| InternLM | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/internlm) |
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| Qwen | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/qwen) |
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| Aquila | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/aquila) |
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| MOSS | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/moss) |
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| Whisper | [link](https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU/HF-Transformers-AutoModels/Model/whisper) |
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```eval_rst
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.. important::
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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>`_.
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```
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```eval_rst
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.. seealso::
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See the complete examples `here <https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/CPU>`_.
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```
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