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Published nm-vllm-ent docker package and added README.md
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# nm-vllm-certs | ||
# nm-vllm-certs | ||
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## Overview | ||
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The `nm-vllm` packages published in this repository are Neuralmagic Enterprise Edition of [vLLM](https://github.com/vllm-project/vllm). Packages are versioned Python wheels and docker images. These are released as "production level" official releases and "beta level" Nightly's. | ||
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Official releases are made at the discretion of Neuralmagic, but typically track with `vllm` releases. These wheels are available via "public pypi" as well as ["nm-pypi"](https://pypi.neuralmagic.com). | ||
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Nightly's are released every night given green runs in automation. The wheels are available at ["nm-pypi"](https://pypi.neuralmagic.com). | ||
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## Installation | ||
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### PyPI | ||
The [nm-vllm PyPi package](https://pypi.neuralmagic.com/simple/nm-vllm/index.html) includes pre-compiled binaries for CUDA (version 12.1) kernels. For other PyTorch or CUDA versions, please compile the package from source. | ||
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Install it using pip: | ||
```bash | ||
pip install nm-vllm --extra-index-url https://pypi.neuralmagic.com/simple | ||
``` | ||
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To utilize the weight sparsity features, include the optional `sparse` dependencies. | ||
```bash | ||
pip install nm-vllm[sparse] --extra-index-url https://pypi.neuralmagic.com/simple | ||
``` | ||
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### Docker | ||
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The [`nm-vllm-ent` container registry](https://github.com/neuralmagic/nm-vllm-certs/pkgs/container/nm-vllm-ent) includes premade docker images. | ||
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Launch the OpenAI-compatible server with: | ||
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```bash | ||
MODEL_ID=Qwen/Qwen2-0.5B-Instruct | ||
docker run --gpus all --shm-size 2g ghcr.io/neuralmagic/nm-vllm-ent:latest --model $MODEL_ID | ||
``` | ||
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## Models | ||
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Neural Magic maintains a variety of optimized models on our Hugging Face organization profiles: | ||
- [neuralmagic](https://huggingface.co/neuralmagic) | ||
- [nm-testing](https://huggingface.co/nm-testing) |