Model Type | autoregressive, language model |
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Use Cases |
Areas: | Research, Code generation |
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Applications: | |
Primary Use Cases: | Generating executable code from English prompts |
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Limitations: | The model is primarily intended for program synthesis., It may not be suitable for tasks outside code generation. |
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Considerations: | Prompts should preferably be in the form of a comment string. |
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Additional Notes | Benchmarks used for evaluation include HumanEval and MTPB. |
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Supported Languages | English (proficient), C (supported), C++ (supported), Go (supported), Java (supported), JavaScript (supported), Python (supported) |
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Training Details |
Data Sources: | BigQuery, GitHub repositories |
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Data Volume: | |
Methodology: | Pre-trained on multiple programming languages |
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Input Output |
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Performance Tips: | Use int8_float16 for CUDA device to optimize performance. |
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Release Notes |
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Notes: | Quantized version of CodeGen-Multi 6B. |
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