Fix repo & documentation URLs (#163)

docs/source/models/adding_model.rst

@@ -11,22 +11,22 @@ This document provides a high-level guide on integrating a `HuggingFace Transfor
     However, for models that include new operators (e.g., a new attention mechanism), the process can be a bit more complex.
 
 .. tip::
-    If you are encountering issues while integrating your model into vLLM, feel free to open an issue on our `GitHub <https://github.com/WoosukKwon/vllm/issues>`_ repository.
+    If you are encountering issues while integrating your model into vLLM, feel free to open an issue on our `GitHub <https://github.com/vllm-project/vllm/issues>`_ repository.
     We will be happy to help you out!
 
 
 0. Fork the vLLM repository
 --------------------------------
 
-Start by forking our `GitHub <https://github.com/WoosukKwon/vllm/issues>`_ repository and then :ref:`build it from source <build_from_source>`.
+Start by forking our `GitHub <https://github.com/vllm-project/vllm/issues>`_ repository and then :ref:`build it from source <build_from_source>`.
 This gives you the ability to modify the codebase and test your model.
 
 
 1. Bring your model code
 ------------------------
 
-Clone the PyTorch model code from the HuggingFace Transformers repository and put it into the `vllm/model_executor/models <https://github.com/WoosukKwon/vllm/tree/main/vllm/model_executor/models>`_ directory.
-For instance, vLLM's `OPT model <https://github.com/WoosukKwon/vllm/blob/main/vllm/model_executor/models/opt.py>`_ was adpated from the HuggingFace's `modeling_opt.py <https://github.com/huggingface/transformers/blob/main/src/transformers/models/opt/modeling_opt.py>`_ file.
+Clone the PyTorch model code from the HuggingFace Transformers repository and put it into the `vllm/model_executor/models <https://github.com/vllm-project/vllm/tree/main/vllm/model_executor/models>`_ directory.
+For instance, vLLM's `OPT model <https://github.com/vllm-project/vllm/blob/main/vllm/model_executor/models/opt.py>`_ was adpated from the HuggingFace's `modeling_opt.py <https://github.com/huggingface/transformers/blob/main/src/transformers/models/opt/modeling_opt.py>`_ file.
 
 .. warning::
     When copying the model code, make sure to review and adhere to the code's copyright and licensing terms.
@@ -91,4 +91,4 @@ While the process is straightforward for most layers, the tensor-parallel layers
 5. Register your model
 ----------------------
 
-Finally, include your :code:`*ForCausalLM` class in `vllm/model_executor/models/__init__.py <https://github.com/WoosukKwon/vllm/blob/main/vllm/model_executor/models/__init__.py>`_ and register it to the :code:`_MODEL_REGISTRY` in `vllm/model_executor/model_loader.py <https://github.com/WoosukKwon/vllm/blob/main/vllm/model_executor/model_loader.py>`_.
+Finally, include your :code:`*ForCausalLM` class in `vllm/model_executor/models/__init__.py <https://github.com/vllm-project/vllm/blob/main/vllm/model_executor/models/__init__.py>`_ and register it to the :code:`_MODEL_REGISTRY` in `vllm/model_executor/model_loader.py <https://github.com/vllm-project/vllm/blob/main/vllm/model_executor/model_loader.py>`_.

docs/source/models/supported_models.rst

@@ -29,7 +29,7 @@ Alongside each architecture, we include some popular models that use it.
 
 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/vllm/issues>`_ project.
+Alternatively, you can raise an issue on our `GitHub <https://github.com/vllm-project/vllm/issues>`_ project.
 
 .. tip::
     The easiest way to check if your model is supported is to run the program below: