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Initial README

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+ # Nebula: Code Generation through Natural Language Understanding
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+ <p align="left">
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+ 📑 <a href="https://huggingface.co/papers/yyyy.yyyyy" target="_blank">Paper</a> &nbsp&nbsp | &nbsp&nbsp 🌐 <a href="https://nebula-codegen.github.io/" target="_blank">Project Page</a> &nbsp&nbsp | &nbsp&nbsp 💾 <a href="https://huggingface.co/collections/toolevalxm/nebula-67b978e28fd926b56a4f55a3" target="_blank">Released Resources</a> &nbsp&nbsp | &nbsp&nbsp 📦 <a href="https://github.com/xmhtoolathlon/Nebula-ModelForge" target="_blank">Repo</a>
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+ We release the base training data for our Nebula code generation models, curated from the original CodeSearchNet corpus maintained by the GitHub research team.
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+ The data format for each line in the `train_code_v3.jsonl` is as follows:
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+ ```
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+ {
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+ "code_snippet": <the original code snippet>,
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+ "docstring": <the natural language documentation>,
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+ "language": <programming language identifier>,
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+ "func_name": <the function name>,
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+ "repo": <source repository name>,
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+ "path": <file path in original repository>,
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+ "metadata": <additional context information>
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+ }
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+ ```
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+ Some entries have truncated docstrings due to maximum length constraints during preprocessing.
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+ *Note: We filtered samples based on code quality metrics. Future versions may include additional quality annotations.