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{{cookiecutter.repo_name}}/README.md

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-# SUPERB Submission Template
-
-This repository can be used to generate a template so you can submit your pretrained model for evaluation on [the leaderboard](https://huggingface.co/spaces/superb/superb-leaderboard) in the [SUPERB Challenge](https://superbbenchmark.org/challenge).
-
-## Quickstart
-
-### 1. Create an account and organisation on the Hugging Face Hub
-
-First create an account on the Hugging Face Hub and you can sign up [here](https://huggingface.co/join) if you haven't already! Next, create a new organization and invite the SUPERB Hidden Set Committee to join. You will upload your model to a repository under this organization so that members inside it can access the model.
-
-* [superb-hidden-set](https://huggingface.co/superb-hidden-set)
-
-### 2. Create a template repository on your machine
-
-The next step is to create a template repository on your local machine that contains various files and a CLI to help you validate and submit your pretrained models. The Hugging Face Hub uses [Git Large File Storage (LFS)](https://git-lfs.github.com) to manage large files, so first install it if you don't have it already. For example, on macOS you can run:
-
-```bash
-brew install git-lfs
-git lfs install
-```
-
-Next, run the following commands to create the repository. We recommend creating a Python virtual environment for the project, e.g. with Anaconda:
-
-```bash
-# Create and activate a virtual environment
-conda create -n superb-submit python=3.8 && conda activate superb-submit
-# Install the following libraries
-pip install cookiecutter huggingface-hub==0.0.16
-# Create the template repository
-cookiecutter git+https://huggingface.co/superb/superb-submission
-```
-
-This will ask you to specify your Hugging Face Hub username, password, organisation, and the name of the repository:
-
-```
-hf_hub_username [<huggingface>]:
-hf_hub_password [<password>]:
-hf_hub_organisation [superb-submissions]:
-repo_name [<my-superb-submissions>]:
-```
-
-This will trigger the following steps:
-
-1. Create a private dataset repository on the Hugging Face Hub under `{hf_hub_organisation}/{repo_name}`
-2. Clone the repository to your local machine
-3. Add various template files, commit them locally to the repository, and push them to the Hub
-
-The resulting repository should have the following structure:
-
-```
-my-superb-submission
-├── LICENSE
-├── README.md               <- The README with submission instructions
-├── cli.py                  <- The CLI for validating predictions etc
-└── requirements.txt        <- The requirements packages for the submissions
-├── expert.py               <- Your model definition
-└── model.pt                <- Your model weights
-```
-
-### 3. Install the dependencies
-
-The final step is to install the project's dependencies:
-
-```bash
-# Navigate to the template repository
-cd my-superb-submission
-# Install dependencies
-python -m pip install -r requirements.txt
-```
-
-That's it! You're now all set to start pretraining your speech models - see the instructions below on how to submit them to the Hub.
-
-
-## Submitting to the leaderboard
-
-To make a submission to the [leaderboard](https://superbbenchmark.org/leaderboard), there are 4 main steps:
-
-1. Modify `expert.py` and `model.py` so we can initialize an upstream model following the [policy](https://superbbenchmark.org/challenge) by:
-
-    ```python
-    upstream = UpstreamExpert(ckpt="./model.pt")
-    ```
-
-2. Validate the upstream model meets the requirements in the [policy](https://superbbenchmark.org/challenge). If everything is correct, you should see the following message: "All submission files validated! Now you can make a submission."
-
-    ```
-    python cli.py validate
-    ```
-
-3. Push the predictions to the Hub! If there are no errors, you should see the following message: "Upload successful!"
-
-    ```
-    python cli.py upload "commit message: my best model"
-    ```
-
-4. [Make a submission at SUPERB website](https://superbbenchmark.org/submit) by uniquely indentifying this submission/model with the following information, which will be shown by:
-
-    ```
-    python cli.py info
-    ```
-
-    - Organization Name
-    - Repository Name
-    - Commit Hash (full 40 characters)
-
-After you finish the above 4 steps. Please stay tuned and wait for us to get the finetuned results on the hidden set!