a8df429985
* initial commit * update llama.cpp * add demo video at first * fix ollama link in readme * meet review * update * small fix
187 lines
25 KiB
Markdown
187 lines
25 KiB
Markdown
> [!IMPORTANT]
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> ***`bigdl-llm` has now become `ipex-llm` (see the migration guide [here](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/bigdl_llm_migration.html)); you may find the original `BigDL` project [here](https://github.com/intel-analytics/BigDL-2.x).***
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---
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# 💫 IPEX-LLM
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**`IPEX-LLM`** is a PyTorch library for running **LLM** on Intel CPU and GPU *(e.g., local PC with iGPU, discrete GPU such as Arc, Flex and Max)* with very low latency[^1].
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> [!NOTE]
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> - *It is built on top of **Intel Extension for PyTorch** (**`IPEX`**), as well as the excellent work of **`llama.cpp`**, **`bitsandbytes`**, **`vLLM`**, **`qlora`**, **`AutoGPTQ`**, **`AutoAWQ`**, etc.*
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> - *It provides seamless integration with [llama.cpp](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/llama_cpp_quickstart.html), [ollama](https://ipex-llm.readthedocs.io/en/main/doc/LLM/Quickstart/ollama_quickstart.html), [Text-Generation-WebUI](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/webui_quickstart.html), [HuggingFace transformers](python/llm/example/GPU/HF-Transformers-AutoModels), [HuggingFace PEFT](python/llm/example/GPU/LLM-Finetuning), [LangChain](python/llm/example/GPU/LangChain), [LlamaIndex](python/llm/example/GPU/LlamaIndex), [DeepSpeed-AutoTP](python/llm/example/GPU/Deepspeed-AutoTP), [vLLM](python/llm/example/GPU/vLLM-Serving), [FastChat](python/llm/src/ipex_llm/serving/fastchat), [HuggingFace TRL](python/llm/example/GPU/LLM-Finetuning/DPO), [AutoGen](python/llm/example/CPU/Applications/autogen), [ModeScope](python/llm/example/GPU/ModelScope-Models), etc.*
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> - ***50+ models** have been optimized/verified on `ipex-llm` (including LLaMA2, Mistral, Mixtral, Gemma, LLaVA, Whisper, ChatGLM, Baichuan, Qwen, RWKV, and more); see the complete list [here](#verified-models).*
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## `ipex-llm` Demo
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See the demo of running [*Text-Generation-WebUI*](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/webui_quickstart.html), [*local RAG using LangChain-Chatchat*](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/chatchat_quickstart.html), [*llama.cpp*](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/llama_cpp_quickstart.html) and [*HuggingFace transformers*](python/llm/example/GPU/HF-Transformers-AutoModels) *(on either Intel Core Ultra laptop or Arc GPU)* with `ipex-llm` below.
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<table width="100%">
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<tr>
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<td align="center" colspan="2"><strong>Intel Core Ultra Laptop</strong></td>
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<td align="center" colspan="2"><strong>Intel Arc GPU</strong></td>
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</tr>
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<tr>
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<td>
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<video src="https://private-user-images.githubusercontent.com/1931082/319632616-895d56cd-e74b-4da1-b4d1-2157df341424.mp4?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.Ga8mmCAO62DFCNzU1fdoyC_4MzqhDHzjZedzmi_2L-I" width=100% controls />
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</td>
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<td>
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<video src="https://private-user-images.githubusercontent.com/1931082/319625142-68da379e-59c6-4308-88e8-c17e40baba7b.mp4?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.g0bYAj3J8IJci7pLzoJI6QDalyzXzMYtQkDY7aqZMc4" width=100% controls />
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</td>
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<td>
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<video src="https://private-user-images.githubusercontent.com/1931082/319625685-ff13b099-bcda-48f1-b11b-05421e7d386d.mp4?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.OFxex8Yj6WyqJKMi6B1Q19KkmbYqYCg1rD49wUwxdXQ" width=100% controls />
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</td>
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<td>
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<video src="https://private-user-images.githubusercontent.com/1931082/319625443-cac77ee6-3a7f-475b-9730-12491105d305.mp4?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.a4O2rJ1nPXH5aSgKV15mbf6Qjs4ysvC-BTRnQmbflIo" width=100% controls />
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</td>
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</tr>
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<tr>
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<td align="center" width="25%">
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<a href="https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/webui_quickstart.html">Text-Generation-WebUI</a>
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</td>
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<td align="center" width="25%">
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<a href="https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/chatchat_quickstart.html">Local RAG using LangChain-Chatchat</a>
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</td>
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<td align="center" width="25%">
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<a href="https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/llama_cpp_quickstart.html">llama.cpp</a>
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</td>
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<td align="center" width="25%">
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<a href="https://github.com/intel-analytics/ipex-llm/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels">HuggingFace transformers</a>
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</td> </tr>
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</table>
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## Latest Update 🔥
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- [2024/04] `ipex-llm` now supports **Llama 3** on both Intel [GPU](python/llm/example/GPU/HF-Transformers-AutoModels/Model/llama3) and [CPU](python/llm/example/CPU/HF-Transformers-AutoModels/Model/llama3).
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- [2024/04] `ipex-llm` now provides C++ interface, which can be used as an accelerated backend for running [llama.cpp](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/llama_cpp_quickstart.html) and [ollama](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/ollama_quickstart.html) on Intel GPU.
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- [2024/03] `bigdl-llm` has now become `ipex-llm` (see the migration guide [here](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/bigdl_llm_migration.html)); you may find the original `BigDL` project [here](https://github.com/intel-analytics/bigdl-2.x).
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- [2024/02] `ipex-llm` now supports directly loading model from [ModelScope](python/llm/example/GPU/ModelScope-Models) ([魔搭](python/llm/example/CPU/ModelScope-Models)).
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- [2024/02] `ipex-llm` added initial **INT2** support (based on llama.cpp [IQ2](python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/GGUF-IQ2) mechanism), which makes it possible to run large-size LLM (e.g., Mixtral-8x7B) on Intel GPU with 16GB VRAM.
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- [2024/02] Users can now use `ipex-llm` through [Text-Generation-WebUI](https://github.com/intel-analytics/text-generation-webui) GUI.
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- [2024/02] `ipex-llm` now supports *[Self-Speculative Decoding](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Inference/Self_Speculative_Decoding.html)*, which in practice brings **~30% speedup** for FP16 and BF16 inference latency on Intel [GPU](python/llm/example/GPU/Speculative-Decoding) and [CPU](python/llm/example/CPU/Speculative-Decoding) respectively.
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- [2024/02] `ipex-llm` now supports a comprehensive list of LLM **finetuning** on Intel GPU (including [LoRA](python/llm/example/GPU/LLM-Finetuning/LoRA), [QLoRA](python/llm/example/GPU/LLM-Finetuning/QLoRA), [DPO](python/llm/example/GPU/LLM-Finetuning/DPO), [QA-LoRA](python/llm/example/GPU/LLM-Finetuning/QA-LoRA) and [ReLoRA](python/llm/example/GPU/LLM-Finetuning/ReLora)).
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- [2024/01] Using `ipex-llm` [QLoRA](python/llm/example/GPU/LLM-Finetuning/QLoRA), we managed to finetune LLaMA2-7B in **21 minutes** and LLaMA2-70B in **3.14 hours** on 8 Intel Max 1550 GPU for [Standford-Alpaca](python/llm/example/GPU/LLM-Finetuning/QLoRA/alpaca-qlora) (see the blog [here](https://www.intel.com/content/www/us/en/developer/articles/technical/finetuning-llms-on-intel-gpus-using-bigdl-llm.html)).
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<details><summary>More updates</summary>
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<br/>
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- [2023/12] `ipex-llm` now supports [ReLoRA](python/llm/example/GPU/LLM-Finetuning/ReLora) (see *["ReLoRA: High-Rank Training Through Low-Rank Updates"](https://arxiv.org/abs/2307.05695)*).
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- [2023/12] `ipex-llm` now supports [Mixtral-8x7B](python/llm/example/GPU/HF-Transformers-AutoModels/Model/mixtral) on both Intel [GPU](python/llm/example/GPU/HF-Transformers-AutoModels/Model/mixtral) and [CPU](python/llm/example/CPU/HF-Transformers-AutoModels/Model/mixtral).
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- [2023/12] `ipex-llm` now supports [QA-LoRA](python/llm/example/GPU/LLM-Finetuning/QA-LoRA) (see *["QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models"](https://arxiv.org/abs/2309.14717)*).
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- [2023/12] `ipex-llm` now supports [FP8 and FP4 inference](python/llm/example/GPU/HF-Transformers-AutoModels/More-Data-Types) on Intel ***GPU***.
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- [2023/11] Initial support for directly loading [GGUF](python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/GGUF), [AWQ](python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/AWQ) and [GPTQ](python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/GPTQ) models into `ipex-llm` is available.
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- [2023/11] `ipex-llm` now supports [vLLM continuous batching](python/llm/example/GPU/vLLM-Serving) on both Intel [GPU](python/llm/example/GPU/vLLM-Serving) and [CPU](python/llm/example/CPU/vLLM-Serving).
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- [2023/10] `ipex-llm` now supports [QLoRA finetuning](python/llm/example/GPU/LLM-Finetuning/QLoRA) on both Intel [GPU](python/llm/example/GPU/LLM-Finetuning/QLoRA) and [CPU](python/llm/example/CPU/QLoRA-FineTuning).
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- [2023/10] `ipex-llm` now supports [FastChat serving](python/llm/src/ipex_llm/llm/serving) on on both Intel CPU and GPU.
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- [2023/09] `ipex-llm` now supports [Intel GPU](python/llm/example/GPU) (including iGPU, Arc, Flex and MAX).
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- [2023/09] `ipex-llm` [tutorial](https://github.com/intel-analytics/ipex-llm-tutorial) is released.
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</details>
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[^1]: Performance varies by use, configuration and other factors. `ipex-llm` may not optimize to the same degree for non-Intel products. Learn more at www.Intel.com/PerformanceIndex.
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## `ipex-llm` Quickstart
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### Install `ipex-llm`
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- [Windows GPU](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/install_windows_gpu.html): installing `ipex-llm` on Windows with Intel GPU
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- [Linux GPU](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/install_linux_gpu.html): installing `ipex-llm` on Linux with Intel GPU
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- [Docker](docker/llm): using `ipex-llm` dockers on Intel CPU and GPU
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- *For more details, please refer to the [installation guide](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Overview/install.html)*
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### Run `ipex-llm`
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- [llama.cpp](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/llama_cpp_quickstart.html): running **llama.cpp** (*using C++ interface of `ipex-llm` as an accelerated backend for `llama.cpp`*) on Intel GPU
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- [ollama](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/ollama_quickstart.html): running **ollama** (*using C++ interface of `ipex-llm` as an accelerated backend for `ollama`*) on Intel GPU
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- [vLLM](python/llm/example/GPU/vLLM-Serving): running `ipex-llm` in `vLLM` on both Intel [GPU](python/llm/example/GPU/vLLM-Serving) and [CPU](python/llm/example/CPU/vLLM-Serving)
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- [FastChat](python/llm/src/ipex_llm/serving/fastchat): running `ipex-llm` in `FastChat` serving on on both Intel GPU and CPU
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- [LangChain-Chatchat RAG](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/chatchat_quickstart.html): running `ipex-llm` in `LangChain-Chatchat` (*Knowledge Base QA using **RAG** pipeline*)
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- [Text-Generation-WebUI](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/webui_quickstart.html): running `ipex-llm` in `oobabooga` **WebUI**
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- [Benchmarking](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/benchmark_quickstart.html): running (latency and throughput) benchmarks for `ipex-llm` on Intel CPU and GPU
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### Code Examples
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- Low bit inference
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- [INT4 inference](python/llm/example/GPU/HF-Transformers-AutoModels/Model): **INT4** LLM inference on Intel [GPU](python/llm/example/GPU/HF-Transformers-AutoModels/Model) and [CPU](python/llm/example/CPU/HF-Transformers-AutoModels/Model)
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- [FP8/FP4 inference](python/llm/example/GPU/HF-Transformers-AutoModels/More-Data-Types): **FP8** and **FP4** LLM inference on Intel [GPU](python/llm/example/GPU/HF-Transformers-AutoModels/More-Data-Types)
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- [INT8 inference](python/llm/example/GPU/HF-Transformers-AutoModels/More-Data-Types): **INT8** LLM inference on Intel [GPU](python/llm/example/GPU/HF-Transformers-AutoModels/More-Data-Types) and [CPU](python/llm/example/CPU/HF-Transformers-AutoModels/More-Data-Types)
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- [INT2 inference](python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/GGUF-IQ2): **INT2** LLM inference (based on llama.cpp IQ2 mechanism) on Intel [GPU](python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/GGUF-IQ2)
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- FP16/BF16 inference
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- **FP16** LLM inference on Intel [GPU](python/llm/example/GPU/Speculative-Decoding), with possible [self-speculative decoding](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Inference/Self_Speculative_Decoding.html) optimization
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- **BF16** LLM inference on Intel [CPU](python/llm/example/CPU/Speculative-Decoding), with possible [self-speculative decoding](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Inference/Self_Speculative_Decoding.html) optimization
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- Save and load
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- [Low-bit models](python/llm/example/CPU/HF-Transformers-AutoModels/Save-Load): saving and loading `ipex-llm` low-bit models
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- [GGUF](python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/GGUF): directly loading GGUF models into `ipex-llm`
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- [AWQ](python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/AWQ): directly loading AWQ models into `ipex-llm`
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- [GPTQ](python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/GPTQ): directly loading GPTQ models into `ipex-llm`
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- Finetuning
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- LLM finetuning on Intel [GPU](python/llm/example/GPU/LLM-Finetuning), including [LoRA](python/llm/example/GPU/LLM-Finetuning/LoRA), [QLoRA](python/llm/example/GPU/LLM-Finetuning/QLoRA), [DPO](python/llm/example/GPU/LLM-Finetuning/DPO), [QA-LoRA](python/llm/example/GPU/LLM-Finetuning/QA-LoRA) and [ReLoRA](python/llm/example/GPU/LLM-Finetuning/ReLora)
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- QLoRA finetuning on Intel [CPU](python/llm/example/CPU/QLoRA-FineTuning)
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- Integration with community libraries
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- [HuggingFace tansformers](python/llm/example/GPU/HF-Transformers-AutoModels)
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- [Standard PyTorch model](python/llm/example/GPU/PyTorch-Models)
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- [DeepSpeed-AutoTP](python/llm/example/GPU/Deepspeed-AutoTP)
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- [HuggingFace PEFT](python/llm/example/GPU/LLM-Finetuning/HF-PEFT)
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- [HuggingFace TRL](python/llm/example/GPU/LLM-Finetuning/DPO)
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- [LangChain](python/llm/example/GPU/LangChain)
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- [LlamaIndex](python/llm/example/GPU/LlamaIndex)
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- [AutoGen](python/llm/example/CPU/Applications/autogen)
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- [ModeScope](python/llm/example/GPU/ModelScope-Models)
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- [Tutorials](https://github.com/intel-analytics/ipex-llm-tutorial)
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*For more details, please refer to the `ipex-llm` document [website](https://ipex-llm.readthedocs.io/).*
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## Verified Models
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Over 50 models have been optimized/verified on `ipex-llm`, including *LLaMA/LLaMA2, Mistral, Mixtral, Gemma, LLaVA, Whisper, ChatGLM2/ChatGLM3, Baichuan/Baichuan2, Qwen/Qwen-1.5, InternLM* and more; see the list below.
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| Model | CPU Example | GPU Example |
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| LLaMA *(such as Vicuna, Guanaco, Koala, Baize, WizardLM, etc.)* | [link1](python/llm/example/CPU/Native-Models), [link2](python/llm/example/CPU/HF-Transformers-AutoModels/Model/vicuna) |[link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/vicuna)|
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| LLaMA 2 | [link1](python/llm/example/CPU/Native-Models), [link2](python/llm/example/CPU/HF-Transformers-AutoModels/Model/llama2) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/llama2) |
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| LLaMA 3 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/llama3) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/llama3) |
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| ChatGLM | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/chatglm) | |
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| ChatGLM2 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/chatglm2) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/chatglm2) |
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| ChatGLM3 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/chatglm3) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/chatglm3) |
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| Mistral | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/mistral) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/mistral) |
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| Mixtral | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/mixtral) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/mixtral) |
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| Falcon | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/falcon) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/falcon) |
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| MPT | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/mpt) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/mpt) |
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| Dolly-v1 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/dolly_v1) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/dolly-v1) |
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| Dolly-v2 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/dolly_v2) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/dolly-v2) |
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| Replit Code| [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/replit) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/replit) |
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| RedPajama | [link1](python/llm/example/CPU/Native-Models), [link2](python/llm/example/CPU/HF-Transformers-AutoModels/Model/redpajama) | |
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| Phoenix | [link1](python/llm/example/CPU/Native-Models), [link2](python/llm/example/CPU/HF-Transformers-AutoModels/Model/phoenix) | |
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| StarCoder | [link1](python/llm/example/CPU/Native-Models), [link2](python/llm/example/CPU/HF-Transformers-AutoModels/Model/starcoder) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/starcoder) |
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| Baichuan | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/baichuan) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/baichuan) |
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| Baichuan2 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/baichuan2) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/baichuan2) |
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| InternLM | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/internlm) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/internlm) |
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| Qwen | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/qwen) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/qwen) |
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| Qwen1.5 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/qwen1.5) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/qwen1.5) |
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| Qwen-VL | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/qwen-vl) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/qwen-vl) |
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| Aquila | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/aquila) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/aquila) |
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| Aquila2 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/aquila2) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/aquila2) |
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| MOSS | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/moss) | |
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| Whisper | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/whisper) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/whisper) |
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| Phi-1_5 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/phi-1_5) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/phi-1_5) |
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| Flan-t5 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/flan-t5) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/flan-t5) |
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| LLaVA | [link](python/llm/example/CPU/PyTorch-Models/Model/llava) | [link](python/llm/example/GPU/PyTorch-Models/Model/llava) |
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| CodeLlama | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/codellama) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/codellama) |
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| Skywork | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/skywork) | |
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| InternLM-XComposer | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/internlm-xcomposer) | |
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| WizardCoder-Python | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/wizardcoder-python) | |
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| CodeShell | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/codeshell) | |
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| Fuyu | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/fuyu) | |
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| Distil-Whisper | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/distil-whisper) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/distil-whisper) |
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| Yi | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/yi) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/yi) |
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| BlueLM | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/bluelm) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/bluelm) |
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| Mamba | [link](python/llm/example/CPU/PyTorch-Models/Model/mamba) | [link](python/llm/example/GPU/PyTorch-Models/Model/mamba) |
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| SOLAR | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/solar) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/solar) |
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| Phixtral | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/phixtral) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/phixtral) |
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| InternLM2 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/internlm2) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/internlm2) |
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| RWKV4 | | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/rwkv4) |
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| RWKV5 | | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/rwkv5) |
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| Bark | [link](python/llm/example/CPU/PyTorch-Models/Model/bark) | [link](python/llm/example/GPU/PyTorch-Models/Model/bark) |
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| SpeechT5 | | [link](python/llm/example/GPU/PyTorch-Models/Model/speech-t5) |
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| DeepSeek-MoE | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/deepseek-moe) | |
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| Ziya-Coding-34B-v1.0 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/ziya) | |
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| Phi-2 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/phi-2) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/phi-2) |
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| Yuan2 | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/yuan2) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/yuan2) |
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| Gemma | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/gemma) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/gemma) |
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| DeciLM-7B | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/deciLM-7b) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/deciLM-7b) |
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| Deepseek | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/deepseek) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/deepseek) |
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| StableLM | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/stablelm) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/stablelm) |
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## Get Support
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- Please report a bug or raise a feature request by opening a [Github Issue](https://github.com/intel-analytics/ipex-llm/issues)
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- Please report a vulnerability by opening a draft [GitHub Security Advisory](https://github.com/intel-analytics/ipex-llm/security/advisories)
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