Model Type | Question-Answer, Token-Classification, Sequence-Classification, Text Generation Inference |
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Use Cases |
Areas: | research, commercial applications |
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Applications: | role play, medical resources, technological development, historical document storage |
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Primary Use Cases: | Constructing shelters, Developing technology, Medical diagnosis and reporting, Historical data retrieval |
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Additional Notes | The model is trained for multi-task operations, utilizing Chain of Thoughts, Agent generation, Mark Down with mermaid, and internal preprocessing with RAG systems for tasks. |
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Supported Languages | en (full), sw (full), ig (full), zu (full), ca (full), es (full), pt (full), ha (full) |
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Training Details |
Data Sources: | |
Methodology: | Chain of thoughts, graph of thoughts, tree of thoughts, dual agent response generation, agent ranking, function calling, self-guiding methods. |
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Context Length: | |
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Release Notes |
Version: | |
Notes: | 32k context window, Rope-theta = 1e6, No Sliding-Window Attention. |
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