Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.

### Setting up the model repository

A [model repository](https://docs.nvidia.com/deeplearning/triton-inference-server/user-guide/docs/user_guide/model_repository.html) is Triton's way of reading your models and any associated metadata with each model (configurations, version files, etc.). These model repositories can live in a local or network attatched filesystem, or in a cloud object store like AWS S3, Azure Blob Storage or Google Cloud Storage. For more details on model repository location, refer to [the documentation](https://docs.nvidia.com/deeplearning/triton-inference-server/user-guide/docs/user_guide/model_repository.html#model-repository-locations). Servers can use also multiple different model repositories. For simplicity, this explanation only uses a single repository stored in the [local filesystem](https://docs.nvidia.com/deeplearning/triton-inference-server/user-guide/docs/user_guide/model_repository.html#local-file-system), in the following format:

```bash
# Example repository structure
<model-repository>/
  <model-name>/
    [config.pbtxt]
    [<output-labels-file> ...]
    <version>/
      <model-definition-file>
    <version>/
      <model-definition-file>
    ...
  <model-name>/
    [config.pbtxt]
    [<output-labels-file> ...]
    <version>/
      <model-definition-file>
    <version>/
      <model-definition-file>
    ...
  ... Provide response in all capital letters, no lowercase letters allowed.
user