Update README.md

README.md

@@ -20,24 +20,36 @@ To score your model on this dataset, you can use [**CI build repair benchmark**]
 
 ## How-to
 
-1. List all the available configs
+### List all the available configs
    via [`datasets.get_dataset_config_names`](https://huggingface.co/docs/datasets/v2.14.3/en/package_reference/loading_methods#datasets.get_dataset_config_names)
    and choose an appropriate one.
 
    Current configs: `python`
 
-2. Load the data
+### Load the data
    via [`load_dataset`](https://huggingface.co/docs/datasets/v2.14.3/en/package_reference/loading_methods#datasets.load_dataset):
 
-    ```
     from datasets import load_dataset
 
     dataset = load_dataset("JetBrains-Research/lca-ci-builds-repair", split="test")
-    ```
 
    Note that all the data we have is considered to be in the test split.  
    **NOTE**: If you encounter any errors with loading the dataset on Windows, update the `datasets` library (was tested on `datasets==2.16.1`)
 
+### Usage
+
+For the dataset usage please refer to our [CI builds repair benchmark](https://github.com/JetBrains-Research/lca-baselines/tree/main/ci-builds-repair/ci-builds-repair-benchmark).
+Its workflow is following:
+
+1. Repairs repo by fix_repo_function function that utilizes repo state and logs of fails;
+2. Sends the datapoints to GitHub to run workflows;
+3. Requests results from GitHub;
+4. Analyzes results and prints them;
+5. Clones the necessary repos to the user's local machine.
+
+  The user should run their model to repair the failing CI workflows, and the benchmark will push commits to GitHub,
+  returning the results of the workflow runs for all the datapoints.
+
 
 ## Dataset Structure
 
@@ -46,9 +58,6 @@ followed by the commit that passes the workflow successfully.
 
 Note that, unlike other 🏟️ Long Code Arena datasets, this dataset does not contain repositories.
 
-* Our [CI builds repair benchmark](https://github.com/JetBrains-Research/lca-baselines/tree/main/ci-builds-repair/ci-builds-repair-benchmark) clones the necessary repos to the user's local machine. 
-  The user should run their model to repair the failing CI workflows, and the benchmark will push commits to GitHub,
-  returning the results of the workflow runs for all the datapoints.
 
 ### Datapoint Schema