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--- |
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license: apache-2.0 |
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language: |
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- en |
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base_model: |
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- microsoft/graphcodebert-base |
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pipeline_tag: text-classification |
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library_name: transformers |
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tags: |
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- code |
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- classification |
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- BERT |
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- transformers |
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- Python |
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- Java |
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- JavaScript |
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--- |
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# Model Card for Model ID |
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## Model Details |
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- **Developed by:** Lavish Kamal Kumar |
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- **Language(s) (NLP):** Python, Java, JavaScript |
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- **License:** Apache 2.0 |
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- **Finetuned from model:** microsoft/graphcodebert-base |
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## Uses |
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This model is a code classifier designed to detect whether a given code snippet is **fast** or **slow** in terms of performance. |
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It is particularly useful for: |
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- Flagging potentially inefficient or unoptimized code |
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- Assisting automated code review tools |
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The model predicts one of two labels: |
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- `LABEL_0`: Slow code (potential performance issues detected) |
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- `LABEL_1`: Fast code (no major performance concerns) |
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It works best on short to medium-length code snippets in supported programming languages and is intended for use with the 🤗 Transformers library. |
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## Supported Languages |
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- Python |
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- Java |
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- JavaScript |
