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README.md
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> [!IMPORTANT]
> ***`bigdl-llm` has now become `ipex-llm` (see the migration guide [here](docs/mddocs/Quickstart/bigdl_llm_migration.md)); you may find the original `BigDL` project [here](https://github.com/intel-analytics/BigDL-2.x).***
> ***`ipex-llm` will soon move to https://github.com/intel/ipex-llm***
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**`IPEX-LLM`** is an LLM acceleration library for Intel [GPU](docs/mddocs/Quickstart/install_windows_gpu.md) *(e.g., local PC with iGPU, discrete GPU such as Arc, Flex and Max)*, [NPU](docs/mddocs/Quickstart/npu_quickstart.md) and CPU [^1].
> [!NOTE]
> - *It is built on top of the excellent work of **`llama.cpp`**, **`transformers`**, **`bitsandbytes`**, **`vLLM`**, **`qlora`**, **`AutoGPTQ`**, **`AutoAWQ`**, etc.*
> - *It provides seamless integration with [llama.cpp](docs/mddocs/Quickstart/llama_cpp_quickstart.md), [Ollama](docs/mddocs/Quickstart/ollama_quickstart.md), [HuggingFace transformers](python/llm/example/GPU/HuggingFace), [LangChain](python/llm/example/GPU/LangChain), [LlamaIndex](python/llm/example/GPU/LlamaIndex), [vLLM](docs/mddocs/Quickstart/vLLM_quickstart.md), [Text-Generation-WebUI](docs/mddocs/Quickstart/webui_quickstart.md), [DeepSpeed-AutoTP](python/llm/example/GPU/Deepspeed-AutoTP), [FastChat](docs/mddocs/Quickstart/fastchat_quickstart.md), [Axolotl](docs/mddocs/Quickstart/axolotl_quickstart.md), [HuggingFace PEFT](python/llm/example/GPU/LLM-Finetuning), [HuggingFace TRL](python/llm/example/GPU/LLM-Finetuning/DPO), [AutoGen](python/llm/example/CPU/Applications/autogen), [ModeScope](python/llm/example/GPU/ModelScope-Models), etc.*
> - *`IPEX-LLM` provides seamless integration with [llama.cpp](docs/mddocs/Quickstart/llama_cpp_quickstart.md), [Ollama](docs/mddocs/Quickstart/ollama_quickstart.md), [HuggingFace transformers](python/llm/example/GPU/HuggingFace), [LangChain](python/llm/example/GPU/LangChain), [LlamaIndex](python/llm/example/GPU/LlamaIndex), [vLLM](docs/mddocs/Quickstart/vLLM_quickstart.md), [Text-Generation-WebUI](docs/mddocs/Quickstart/webui_quickstart.md), [DeepSpeed-AutoTP](python/llm/example/GPU/Deepspeed-AutoTP), [FastChat](docs/mddocs/Quickstart/fastchat_quickstart.md), [Axolotl](docs/mddocs/Quickstart/axolotl_quickstart.md), [HuggingFace PEFT](python/llm/example/GPU/LLM-Finetuning), [HuggingFace TRL](python/llm/example/GPU/LLM-Finetuning/DPO), [AutoGen](python/llm/example/CPU/Applications/autogen), [ModeScope](python/llm/example/GPU/ModelScope-Models), etc.*
> - ***70+ models** have been optimized/verified on `ipex-llm` (e.g., Llama, Phi, Mistral, Mixtral, Whisper, Qwen, MiniCPM, Qwen-VL, MiniCPM-V and more), with state-of-art **LLM optimizations**, **XPU acceleration** and **low-bit (FP8/FP6/FP4/INT4) support**; see the complete list [here](#verified-models).*
## Latest Update 🔥

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README.zh-CN.md
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> [!IMPORTANT]
> `bigdl-llm` 现已更名为 `ipex-llm` (请参阅[此处](docs/mddocs/Quickstart/bigdl_llm_migration.md)的迁移指南); 你可以在[此处](https://github.com/intel-analytics/BigDL-2.x)找到原始的 BigDL 项目。
> ***`ipex-llm` 将会迁移至 https://github.com/intel/ipex-llm***
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**`ipex-llm`** 是一个将大语言模型高效地运行于 Intel [GPU](docs/mddocs/Quickstart/install_windows_gpu.md) *(如搭载集成显卡的个人电脑，Arc 独立显卡、Flex 及 Max 数据中心 GPU 等)*、[NPU](docs/mddocs/Quickstart/npu_quickstart.md) 和 CPU 上的大模型 XPU 加速库[^1]。
> [!NOTE]
> - *它构建在 **`llama.cpp`**, **`transformers`**, **`bitsandbytes`**, **`vLLM`**, **`qlora`**, **`AutoGPTQ`**, **`AutoAWQ`** 等优秀工作之上。*
> - *它可以与 [llama.cpp](docs/mddocs/Quickstart/llama_cpp_quickstart.zh-CN.md), [Ollama](docs/mddocs/Quickstart/ollama_quickstart.zh-CN.md), [HuggingFace transformers](python/llm/example/GPU/HuggingFace), [LangChain](python/llm/example/GPU/LangChain), [LlamaIndex](python/llm/example/GPU/LlamaIndex), [vLLM](docs/mddocs/Quickstart/vLLM_quickstart.md), [Text-Generation-WebUI](docs/mddocs/Quickstart/webui_quickstart.md), [DeepSpeed-AutoTP](python/llm/example/GPU/Deepspeed-AutoTP), [FastChat](docs/mddocs/Quickstart/fastchat_quickstart.md), [Axolotl](docs/mddocs/Quickstart/axolotl_quickstart.md), [HuggingFace PEFT](python/llm/example/GPU/LLM-Finetuning), [HuggingFace TRL](python/llm/example/GPU/LLM-Finetuning/DPO), [AutoGen](python/llm/example/CPU/Applications/autogen), [ModeScope](python/llm/example/GPU/ModelScope-Models) 等无缝衔接。*
> - *`ipex-llm`可以与 [llama.cpp](docs/mddocs/Quickstart/llama_cpp_quickstart.zh-CN.md), [Ollama](docs/mddocs/Quickstart/ollama_quickstart.zh-CN.md), [HuggingFace transformers](python/llm/example/GPU/HuggingFace), [LangChain](python/llm/example/GPU/LangChain), [LlamaIndex](python/llm/example/GPU/LlamaIndex), [vLLM](docs/mddocs/Quickstart/vLLM_quickstart.md), [Text-Generation-WebUI](docs/mddocs/Quickstart/webui_quickstart.md), [DeepSpeed-AutoTP](python/llm/example/GPU/Deepspeed-AutoTP), [FastChat](docs/mddocs/Quickstart/fastchat_quickstart.md), [Axolotl](docs/mddocs/Quickstart/axolotl_quickstart.md), [HuggingFace PEFT](python/llm/example/GPU/LLM-Finetuning), [HuggingFace TRL](python/llm/example/GPU/LLM-Finetuning/DPO), [AutoGen](python/llm/example/CPU/Applications/autogen), [ModeScope](python/llm/example/GPU/ModelScope-Models) 等无缝衔接。*
> - ***70+** 模型已经在 `ipex-llm` 上得到优化和验证（如 Llama, Phi, Mistral, Mixtral, Whisper, Qwen, MiniCPM, Qwen-VL, MiniCPM-V 等), 以获得先进的 **大模型算法优化**, **XPU 加速** 以及 **低比特（FP8FP8/FP6/FP4/INT4) 支持**；更多模型信息请参阅[这里](#模型验证)。*
## 最新更新 🔥