| --- |
| license: apache-2.0 |
| language: |
| - en |
| base_model: |
| - microsoft/graphcodebert-base |
| pipeline_tag: text-classification |
| library_name: transformers |
| tags: |
| - code |
| - classification |
| - BERT |
| - transformers |
| - Python |
| - Java |
| - JavaScript |
| --- |
| # Model Card for Model ID |
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| ## Model Details |
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| - **Developed by:** Lavish Kamal Kumar |
| - **Language(s) (NLP):** Python, Java, JavaScript |
| - **License:** Apache 2.0 |
| - **Finetuned from model:** microsoft/graphcodebert-base |
|
|
| ## Uses |
| 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 |
| - 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) |
| - `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 |
| - Python |
| - Java |
| - JavaScript |
