Dictalm2.0 Instruct Fine Tuned is an open-source language model by ronigold. Features: 7.3b LLM, VRAM: 14.5GB, Context: 32K, License: mit, Instruction-Based, Merged, LLM Explorer Score: 0.12.
Dictalm2.0 Instruct Fine Tuned Parameters and Internals
Model Type Transformer-based, fine-tuned
Use Cases
Areas: Educational, Informational applications
Primary Use Cases: Generating contextual question-answer pairs from textual content
Limitations: Not intended for factual accuracy in critical areas like medical or legal advice
Additional Notes The model is part of a broader initiative to enhance NLP capabilities in the Hebrew language.
Supported Languages Training Details
Data Sources: Synthetic dataset generated from Hebrew Wikipedia
Methodology: Specific loss functions and optimization strategies used for fine-tuning.
Hardware Used: Model Architecture: Transformer-based architecture with optimizations for question generation and answering.
Responsible Ai Considerations
Mitigation Strategies: Use with human oversight for accuracy and appropriateness in sensitive applications.
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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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