mirror of
https://git.datalinker.icu/vllm-project/vllm.git
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100 lines
5.4 KiB
Markdown
100 lines
5.4 KiB
Markdown
<p align="center">
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<picture>
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<source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/vllm-project/vllm/main/docs/source/assets/logos/vllm-logo-text-dark.png">
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<img alt="vLLM" src="https://raw.githubusercontent.com/vllm-project/vllm/main/docs/source/assets/logos/vllm-logo-text-light.png" width=55%>
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</picture>
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</p>
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<h3 align="center">
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Easy, fast, and cheap LLM serving for everyone
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</h3>
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<p align="center">
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| <a href="https://docs.vllm.ai"><b>Documentation</b></a> | <a href="https://vllm.ai"><b>Blog</b></a> | <a href="https://arxiv.org/abs/2309.06180"><b>Paper</b></a> | <a href="https://discord.gg/jz7wjKhh6g"><b>Discord</b></a> |
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</p>
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---
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*Latest News* 🔥
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- [2023/12] Added ROCm support to vLLM.
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- [2023/10] We hosted [the first vLLM meetup](https://lu.ma/first-vllm-meetup) in SF! Please find the meetup slides [here](https://docs.google.com/presentation/d/1QL-XPFXiFpDBh86DbEegFXBXFXjix4v032GhShbKf3s/edit?usp=sharing).
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- [2023/09] We created our [Discord server](https://discord.gg/jz7wjKhh6g)! Join us to discuss vLLM and LLM serving! We will also post the latest announcements and updates there.
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- [2023/09] We released our [PagedAttention paper](https://arxiv.org/abs/2309.06180) on arXiv!
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- [2023/08] We would like to express our sincere gratitude to [Andreessen Horowitz](https://a16z.com/2023/08/30/supporting-the-open-source-ai-community/) (a16z) for providing a generous grant to support the open-source development and research of vLLM.
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- [2023/07] Added support for LLaMA-2! You can run and serve 7B/13B/70B LLaMA-2s on vLLM with a single command!
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- [2023/06] Serving vLLM On any Cloud with SkyPilot. Check out a 1-click [example](https://github.com/skypilot-org/skypilot/blob/master/llm/vllm) to start the vLLM demo, and the [blog post](https://blog.skypilot.co/serving-llm-24x-faster-on-the-cloud-with-vllm-and-skypilot/) for the story behind vLLM development on the clouds.
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- [2023/06] We officially released vLLM! FastChat-vLLM integration has powered [LMSYS Vicuna and Chatbot Arena](https://chat.lmsys.org) since mid-April. Check out our [blog post](https://vllm.ai).
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---
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vLLM is a fast and easy-to-use library for LLM inference and serving.
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vLLM is fast with:
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- State-of-the-art serving throughput
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- Efficient management of attention key and value memory with **PagedAttention**
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- Continuous batching of incoming requests
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- Quantization: [GPTQ](https://arxiv.org/abs/2210.17323), [AWQ](https://arxiv.org/abs/2306.00978), [SqueezeLLM](https://arxiv.org/abs/2306.07629)
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- Optimized CUDA kernels
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vLLM is flexible and easy to use with:
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- Seamless integration with popular Hugging Face models
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- High-throughput serving with various decoding algorithms, including *parallel sampling*, *beam search*, and more
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- Tensor parallelism support for distributed inference
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- Streaming outputs
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- OpenAI-compatible API server
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- Support NVIDIA GPUs and AMD GPUs.
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vLLM seamlessly supports many Hugging Face models, including the following architectures:
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- Aquila & Aquila2 (`BAAI/AquilaChat2-7B`, `BAAI/AquilaChat2-34B`, `BAAI/Aquila-7B`, `BAAI/AquilaChat-7B`, etc.)
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- Baichuan & Baichuan2 (`baichuan-inc/Baichuan2-13B-Chat`, `baichuan-inc/Baichuan-7B`, etc.)
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- BLOOM (`bigscience/bloom`, `bigscience/bloomz`, etc.)
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- ChatGLM (`THUDM/chatglm2-6b`, `THUDM/chatglm3-6b`, etc.)
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- Falcon (`tiiuae/falcon-7b`, `tiiuae/falcon-40b`, `tiiuae/falcon-rw-7b`, etc.)
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- GPT-2 (`gpt2`, `gpt2-xl`, etc.)
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- GPT BigCode (`bigcode/starcoder`, `bigcode/gpt_bigcode-santacoder`, etc.)
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- GPT-J (`EleutherAI/gpt-j-6b`, `nomic-ai/gpt4all-j`, etc.)
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- GPT-NeoX (`EleutherAI/gpt-neox-20b`, `databricks/dolly-v2-12b`, `stabilityai/stablelm-tuned-alpha-7b`, etc.)
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- InternLM (`internlm/internlm-7b`, `internlm/internlm-chat-7b`, etc.)
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- LLaMA & LLaMA-2 (`meta-llama/Llama-2-70b-hf`, `lmsys/vicuna-13b-v1.3`, `young-geng/koala`, `openlm-research/open_llama_13b`, etc.)
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- Mistral (`mistralai/Mistral-7B-v0.1`, `mistralai/Mistral-7B-Instruct-v0.1`, etc.)
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- Mixtral (`mistralai/Mixtral-8x7B-v0.1`, `mistralai/Mixtral-8x7B-Instruct-v0.1`, etc.)
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- MPT (`mosaicml/mpt-7b`, `mosaicml/mpt-30b`, etc.)
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- OPT (`facebook/opt-66b`, `facebook/opt-iml-max-30b`, etc.)
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- Phi-1.5 (`microsoft/phi-1_5`, etc.)
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- Qwen (`Qwen/Qwen-7B`, `Qwen/Qwen-7B-Chat`, etc.)
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- Yi (`01-ai/Yi-6B`, `01-ai/Yi-34B`, etc.)
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Install vLLM with pip or [from source](https://vllm.readthedocs.io/en/latest/getting_started/installation.html#build-from-source):
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```bash
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pip install vllm
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```
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## Getting Started
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Visit our [documentation](https://vllm.readthedocs.io/en/latest/) to get started.
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- [Installation](https://vllm.readthedocs.io/en/latest/getting_started/installation.html)
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- [Quickstart](https://vllm.readthedocs.io/en/latest/getting_started/quickstart.html)
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- [Supported Models](https://vllm.readthedocs.io/en/latest/models/supported_models.html)
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## Contributing
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We welcome and value any contributions and collaborations.
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Please check out [CONTRIBUTING.md](./CONTRIBUTING.md) for how to get involved.
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## Citation
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If you use vLLM for your research, please cite our [paper](https://arxiv.org/abs/2309.06180):
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```bibtex
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@inproceedings{kwon2023efficient,
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title={Efficient Memory Management for Large Language Model Serving with PagedAttention},
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author={Woosuk Kwon and Zhuohan Li and Siyuan Zhuang and Ying Sheng and Lianmin Zheng and Cody Hao Yu and Joseph E. Gonzalez and Hao Zhang and Ion Stoica},
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booktitle={Proceedings of the ACM SIGOPS 29th Symposium on Operating Systems Principles},
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year={2023}
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}
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```
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