Change the name to vLLM (#150)

docs/source/models/supported_models.rst

@@ -3,8 +3,8 @@
 Supported Models
 ================
 
-CacheFlow supports a variety of generative Transformer models in `HuggingFace Transformers <https://github.com/huggingface/transformers>`_.
-The following is the list of model architectures that are currently supported by CacheFlow.
+vLLM supports a variety of generative Transformer models in `HuggingFace Transformers <https://github.com/huggingface/transformers>`_.
+The following is the list of model architectures that are currently supported by vLLM.
 Alongside each architecture, we include some popular models that use it.
 
 .. list-table::
@@ -22,19 +22,19 @@ Alongside each architecture, we include some popular models that use it.
   * - :code:`OPTForCausalLM`
     - OPT, OPT-IML
 
-If your model uses one of the above model architectures, you can seamlessly run your model with CacheFlow.
+If your model uses one of the above model architectures, you can seamlessly run your model with vLLM.
 Otherwise, please refer to :ref:`Adding a New Model <adding_a_new_model>` for instructions on how to implement support for your model.
-Alternatively, you can raise an issue on our `GitHub <https://github.com/WoosukKwon/cacheflow/issues>`_ project.
+Alternatively, you can raise an issue on our `GitHub <https://github.com/WoosukKwon/vllm/issues>`_ project.
 
 .. tip::
     The easiest way to check if your model is supported is to run the program below:
 
     .. code-block:: python
 
-        from cacheflow import LLM
+        from vllm import LLM
 
         llm = LLM(model=...)  # Name or path of your model
         output = llm.generate("Hello, my name is")
         print(output)
 
-    If CacheFlow successfully generates text, it indicates that your model is supported.
+    If vLLM successfully generates text, it indicates that your model is supported.