| | --- |
| | license: apache-2.0 |
| | language: |
| | - en |
| | base_model: |
| | - microsoft/codebert-base |
| | pipeline_tag: text-classification |
| | library_name: transformers |
| | tags: |
| | - code |
| | - transformers |
| | - classification |
| | - BERT |
| | - Python |
| | - Java |
| | - JavaScript |
| | --- |
| | # Model Card for Model ID |
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| | ## Model Details |
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| | ### Model Description |
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| | <!-- Provide a longer summary of what this model is. --> |
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| | - **Developed by:** Lavish Kamal Kumar |
| | - **License:** Apache 2.0 |
| | - **Finetuned from model:** microsoft/codebert-base |
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| | ## 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: |
| | - Flagging potentially inefficient or unoptimized code |
| | - Assisting automated code review tools |
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| | The model predicts one of two labels: |
| | - `LABEL_0`: Fast code (no major performance concerns) |
| | - `LABEL_1`: Slow code (potential performance issues detected) |
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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 |
