update readme

README.md

@@ -1,53 +1,6 @@
-# Create a new service (generic) template
+# Classification benchmark service
 
-This repository contains the Python + FastAPI template to create a service
-without a model or from an existing model compatible with the Core engine.
-
-Please read the documentation at
-<https://docs.swiss-ai-center.ch/how-to-guides/how-to-create-a-new-service> to
-understand how to use this template.
-
-## Guidelines
-
-TODO: Add instructions on how to edit this template.
-
-### Publishing and deploying using a CI/CD pipeline
-
-This is the recommended way to publish and deploy your service if you have
-access to GitHub Actions or GitLab CI.
-
-TODO
-
-### Publishing and deploying manually
-
-This is the recommended way to publish and deploy your service if you do not
-have access to GitHub Actions or GitLab CI or do not want to use these services.
-
-TODO
-
-## Checklist
-
-These checklists allow you to ensure everything is set up correctly.
-
-### Common tasks
-
-- [ ] Rename the project in the [`pyproject.toml`](./pyproject.toml) file
-- [x] Add files that must be ignored to the [`.gitignore`](.gitignore) configuration file
-- [ ] TODO
-
-### Publishing and deploying using a CI/CD pipeline
-
-> [!NOTE]  
-> This checklist is specific to the _Publishing and deploying using a CI/CD
-> pipeline_ section.
-
-- [x] Add the environment variables
-- [ ] TODO
-
-### Publishing and deploying manually
-
-> [!NOTE]  
-> This checklist is specific to the _Publishing and deploying manually_ section.
-
-- [x] Edit the [`.env`](.env) configuration file
-- [ ] TODO
+This service uses lazypredict benchmarks a dataset with various models and outputs the results sorted by accuracy.
+In order for the service to work your dataset label column must be called "target".
+Also to improve the results you may want to remove uneccessary columns from the dataset.
+Finally, avoid having multiple empty lines at the end of the file.