Question-Answer, Token-Classification, Sequence-Classification, Text Generation Inference
Use Cases
Areas:
research, commercial applications
Applications:
role play, medical resources, technological development, historical document storage
Primary Use Cases:
Constructing shelters, Developing technology, Medical diagnosis and reporting, Historical data retrieval
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.
Supported Languages
en (full), sw (full), ig (full), zu (full), ca (full), es (full), pt (full), ha (full)
Training Details
Data Sources:
Hugging Face hub, Kaggle
Methodology:
Chain of thoughts, graph of thoughts, tree of thoughts, dual agent response generation, agent ranking, function calling, self-guiding methods.
Context Length:
32000
Release Notes
Version:
v0.1
Notes:
32k context window, Rope-theta = 1e6, No Sliding-Window Attention.
Note: green Score (e.g. "73.2") means that the model is better than LeroyDyer/QuietStar_Project.
Rank the QuietStar Project Capabilities
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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation
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