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12
README.md
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@ -10,7 +10,7 @@ Easy, fast, and cheap LLM serving for everyone
</h3>
<p align="center">
| <a href="https://vllm.readthedocs.io/en/latest/"><b>Documentation</b></a> | <a href=""><b>Blog</b></a> |
| <a href="https://vllm.readthedocs.io/en/latest/"><b>Documentation</b></a> | <a href="https://vllm.ai"><b>Blog</b></a> | <a href="https://github.com/vllm-project/vllm/discussions"><b>Discussions</b></a> |
</p>
@ -18,7 +18,7 @@ Easy, fast, and cheap LLM serving for everyone
*Latest News* 🔥
- [2023/06] We officially released vLLM! vLLM has powered [LMSYS Vicuna and Chatbot Arena](https://chat.lmsys.org) since mid April. Check out our [blog post]().
- [2023/06] We officially released vLLM! vLLM has powered [LMSYS Vicuna and Chatbot Arena](https://chat.lmsys.org) since mid April. Check out our [blog post](https://vllm.ai).
---
@ -62,7 +62,7 @@ Visit our [documentation](https://vllm.readthedocs.io/en/latest/) to get started
## Performance
vLLM outperforms HuggingFace Transformers (HF) by up to 24x and Text Generation Inference (TGI) by up to 3.5x, in terms of throughput.
For details, check out our [blog post]().
For details, check out our [blog post](https://vllm.ai).
<p align="center">
<picture>
@ -70,7 +70,7 @@ For details, check out our [blog post]().
<img src="https://raw.githubusercontent.com/vllm-project/vllm/main/docs/source/assets/figures/perf_a10g_n1_light.png" width="45%">
</picture>
<picture>
<source media="(prefers-color-scheme: dark)" srcset="./docs/source/assets/figures/perf_a100_n1_dark.png">
<source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/vllm-project/vllm/main/docs/source/assets/figures/perf_a100_n1_dark.png">
<img src="https://raw.githubusercontent.com/vllm-project/vllm/main/docs/source/assets/figures/perf_a100_n1_light.png" width="45%">
</picture>
<br>
@ -79,11 +79,11 @@ For details, check out our [blog post]().
<p align="center">
<picture>
<source media="(prefers-color-scheme: dark)" srcset="./docs/source/assets/figures/perf_a10g_n3_dark.png">
<source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/vllm-project/vllm/main/docs/source/assets/figures/perf_a10g_n3_dark.png">
<img src="https://raw.githubusercontent.com/vllm-project/vllm/main/docs/source/assets/figures/perf_a10g_n3_light.png" width="45%">
</picture>
<picture>
<source media="(prefers-color-scheme: dark)" srcset="./docs/source/assets/figures/perf_a100_n3_dark.png">
<source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/vllm-project/vllm/main/docs/source/assets/figures/perf_a100_n3_dark.png">
<img src="https://raw.githubusercontent.com/vllm-project/vllm/main/docs/source/assets/figures/perf_a100_n3_light.png" width="45%">
</picture> <br>
<em> Serving throughput when each request asks for 3 output completions. </em>

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docs/source/index.rst
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@ -40,7 +40,7 @@ vLLM is flexible and easy to use with:
* Streaming outputs
* OpenAI-compatible API server
For more information, please refer to our `blog post <>`_.
For more information, please refer to our `blog post <https://vllm.ai>`_.
Documentation

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docs/source/models/adding_model.rst
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@ -18,7 +18,7 @@ This document provides a high-level guide on integrating a `HuggingFace Transfor
0. Fork the vLLM repository
--------------------------------
Start by forking our `GitHub <https://github.com/vllm-project/vllm/issues>`_ repository and then :ref:`build it from source <build_from_source>`.
Start by forking our `GitHub <https://github.com/vllm-project/vllm/>`_ repository and then :ref:`build it from source <build_from_source>`.
This gives you the ability to modify the codebase and test your model.