Update src/tasks_content.py
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src/tasks_content.py
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@@ -44,20 +44,21 @@ TASKS_DESCRIPTIONS = {
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"library_usage": "cool description for Library Usage Examples Generation task",
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"project_code_completion": """# Project-Level Code Completion\n
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We use standard Exact Match (EM) metric for one-line code completion.
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We evaluate Exact Match for different line categories
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For further details on the dataset and the baselines from ποΈ 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).
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""",
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"library_usage": "cool description for Library Usage Examples Generation task",
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"project_code_completion": """# Project-Level Code Completion\n
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Our Project-Level Code Completion π€ [JetBrains-Research/lca-code-completion](https://huggingface.co/datasets/JetBrains-Research/lca-code-completion) includes four datasets:
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* `small-context`: 144 data points,
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* `medium-context`: 224 data points,
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* `large-context`: 270 data points,
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* `huge-context`: 296 data points.
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We use standard Exact Match (EM) metric for one-line code completion.
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We evaluate Exact Match for different line categories:
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* *infile* β functions and classes are from the completion file;
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* *inproject* β functions and files are from the repository snapshot;
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* *committed* β functions and classes are from the files that were added on the completion file commit;
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* *common* β functions and classes with common names, e.g., `main`, `get`, etc.;
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* *non-informative* β short/long lines, import/print lines, or comment lines;
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* *random* β lines that doesn't fit to any of previous categories.
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For further details on the dataset and the baselines from ποΈ 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).
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""",
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