Model Type | |
Use Cases |
Areas: | text generation, code completion |
|
Applications: | programming, software development |
|
Primary Use Cases: | single/multiline code completion |
|
Limitations: | primarily trained on English source code, may produce suboptimal code, may contain bugs or exploits |
|
Considerations: | present a function signature and docstring to get accurate code completion |
|
|
Additional Notes | Model trained only on Python, Java, and Javascript subsets. |
|
Supported Languages | Python (high), Java (high), JavaScript (high) |
|
Training Details |
Data Sources: | Starcoder Training Dataset |
|
Data Volume: | |
Methodology: | Grouped Query Attention, Fill-in-the-Middle training objective |
|
Context Length: | |
Model Architecture: | Neural Architecture Search-based technology, AutoNAC |
|
|
Input Output |
Input Format: | code snippets with comments or function signatures |
|
Accepted Modalities: | |
Output Format: | |
Performance Tips: | Use up to 2048 tokens in the context window for optimal performance. |
|
|