Model Type | text-generation, natural language to SQL conversion |
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Use Cases |
Areas: | Research, Commercial applications |
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Primary Use Cases: | Natural language to SQL generation tasks |
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Limitations: | Requires tuning on specific schemas for optimal performance. |
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Additional Notes | Fine-tuning on a given schema enhances performance. |
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Supported Languages | en (Primary language for model tasks) |
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Training Details |
Data Sources: | 20,000 human-curated questions based on 10 different schemas |
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Methodology: | Fine-tuned on a base StarCoder model |
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Hardware Used: | Tested on an A100 40GB GPU with bfloat16 weights |
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Input Output |
Input Format: | Formatted prompt with task and database schema. |
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Accepted Modalities: | |
Output Format: | |
Performance Tips: | Using specific schema tuning enhances model performance. |
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