Update README.md

Updating README file with more information about the repo and the files.

README.md

@@ -9,5 +9,42 @@ app_file: app.py
 pinned: false
 license: apache-2.0
 ---
+# About this space
+This HF space is a 'Gradio' based space with the configuration above.
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+# Cloning the space repo 
+`git clone https://huggingface.co/spaces/valory/olas-prediction-leaderboard`
+
+# Updating the space repo
+Update the space like any github repo
+Make sure you have git-lfs (since the CSVs are big and need LFS to push)
+Use similar `git` functions to push
+
+# Re-starting the space repo
+There are two ways:
+1. Push a small commit
+2. Use the `Restart this space` from the [settings](https://huggingface.co/spaces/valory/olas-prediction-leaderboard/settings) page
+
+# Running the benchmark to contribute with new data
+Run the benchmark locally using this [repo](https://github.com/valory-xyz/olas-predict-benchmark)
+Please see the readme on the repo on how to run
+Copy the relevant row/columns from `summary.csv` in the results folder
+Paste the CSV in the root of the `olas-prediction-leaderboard` HF space repo as `formatted_data.csv` 
+Add the changes and push using `git add, commit, and push` commands
+Note: you just need to add the new data as a new row in the csv file. One row per model/tool.
+
+# Scripts of the repository
+## app.py
+Starts the gradio app
+Also, kickstart the start.py
+There are 4 tabs:
+1. Benchmark Leaderboard: Shows the benchmark data
+2. About: Some FAQs
+3. Contribute: Some details on how to contribute
+4. Run the benchmark: Run the benchmark on any tools. You will have to provide your api keys 
+
+## start.py
+Setups the necessary things including - Olas-predict-benchmark repo, mech repo, and the required datasets for running the benchmark
+