Update src/tasks_content.py

src/tasks_content.py

@@ -44,20 +44,20 @@ TASKS_DESCRIPTIONS = {
     "library_usage": "cool description for Library Usage Examples Generation task",
     
     "project_code_completion": """# Project-Level Code Completion\n
-        Our Project-Level Code Completion 🤗 [JetBrains-Research/lca-code-completion](https://huggingface.co/datasets/JetBrains-Research/lca-code-completion) includes four datasets: 
-             - `small-context`: 144 data points, 
-             - `medium-context: 224 data points,
-             - `large-context`: 270 data points,
-             - `huge-context`: 296 data points.
+        Our Project-Level Code Completion 🤗 [JetBrains-Research/lca-code-completion](https://huggingface.co/datasets/JetBrains-Research/lca-code-completion) includes four datasets:\n
+        \t * `small-context`: 144 data points,\n
+        \t * `medium-context`: 224 data points,\n
+        \t * `large-context`: 270 data points,\n
+        \t * `huge-context`: 296 data points.\n
 
         We use standard Exact Match (EM) metric for one-line code completion.
-        We evaluate Exact Match for different line categories:
-            - *infile* – functions and classes are from the completion file;
-            - *inproject – functions and files are from the repository snapshot;
-            - *committed* – functions and classes are from the files that were added on the completion file commit;
-            - *common* – functions and classes with common names, e.g., `main`, `get`, etc.;
-            - *non-informative* – short/long lines, import/print lines, or comment lines;
-            - *random* – lines that doesn't fit to any of previous categories.
+        We evaluate Exact Match for different line categories:\n
+        \t * *infile* – functions and classes are from the completion file;\n
+        \t * *inproject* – functions and files are from the repository snapshot;\n
+        \t * *committed* – functions and classes are from the files that were added on the completion file commit;\n
+        \t * *common* – functions and classes with common names, e.g., `main`, `get`, etc.;\n
+        \t * *non-informative* – short/long lines, import/print lines, or comment lines;\n
+        \t * *random* – lines that doesn't fit to any of previous categories.\n
 
         For further details on the dataset and the baselines from 🏟️ Long Code Arena Team, refer to `code_completion` folder in [our baselines repository](https://github.com/JetBrains-Research/lca-baselines) or to our preprint (TODO).
         """,