Add logo and polish readme (#156)

docs/source/index.rst

@@ -1,18 +1,43 @@
 Welcome to vLLM!
 ================
 
-**vLLM** is a fast and easy-to-use library for LLM inference and serving.
-Its core features include:
+.. figure:: ./assets/logos/vllm-logo-text-light.png
+  :width: 60%
+  :align: center
+  :alt: vLLM
+  :class: no-scaled-link
 
-- State-of-the-art performance in serving throughput
-- Efficient management of attention key and value memory with **PagedAttention**
-- Seamless integration with popular HuggingFace models
-- Dynamic batching of incoming requests
-- Optimized CUDA kernels
-- High-throughput serving with various decoding algorithms, including *parallel sampling* and *beam search*
-- Tensor parallelism support for distributed inference
-- Streaming outputs
-- OpenAI-compatible API server
+.. raw:: html
+
+   <p style="text-align:center">
+   <strong>Easy, fast, and cheap LLM serving for everyone
+   </strong>
+   </p>
+
+   <p style="text-align:center">
+   <a class="github-button" href="https://github.com/WoosukKwon/vllm" data-show-count="true" data-size="large" aria-label="Star skypilot-org/skypilot on GitHub">Star</a>
+   <a class="github-button" href="https://github.com/WoosukKwon/vllm/subscription" data-icon="octicon-eye" data-size="large" aria-label="Watch skypilot-org/skypilot on GitHub">Watch</a>
+   <a class="github-button" href="https://github.com/WoosukKwon/vllm/fork" data-icon="octicon-repo-forked" data-size="large" aria-label="Fork skypilot-org/skypilot on GitHub">Fork</a>
+   </p>
+
+
+
+vLLM is a fast and easy to use library for LLM inference and serving.
+
+vLLM is fast with:
+
+* State-of-the-art serving throughput
+* Efficient management of attention key and value memory with **PagedAttention**
+* Dynamic batching of incoming requests
+* Optimized CUDA kernels
+
+vLLM is flexible and easy to use with:
+
+* Seamless integration with popular HuggingFace models
+* High-throughput serving with various decoding algorithms, including *parallel sampling*, *beam search*, and more
+* Tensor parallelism support for distributed inference
+* Streaming outputs
+* OpenAI-compatible API server
 
 For more information, please refer to our `blog post <>`_.