TeenyTinyLlama 460M Chat AWQ is an open-source language model by nicholasKluge. Features: 460m LLM, VRAM: 0.3GB, Context: 2K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.11.
TeenyTinyLlama 460M Chat AWQ Parameters and Internals
Model Type text generation, conversation, assistant
Use Cases
Areas: Research on low-resource language modeling
Applications: Scientific experiments, Fine-tuning for deployment
Primary Use Cases: Understand challenges related to developing language models in low-resource languages
Limitations: Not intended for deployment, Not suitable for human-facing interactions, Not suitable for translation or generating text in other languages
Considerations: Users are warned of risks, biases, and the need for human moderation.
Additional Notes Use CAUTION in deploying as it inherits general language model biases and behaviors.
Supported Languages Brazilian Portuguese (high)
Training Details
Data Sources: nicholasKluge/instruct-aira-dataset-v2
Data Volume:
Methodology:
Hardware Used:
Model Architecture: quantized version using AutoAWQ
Responsible Ai Considerations
Fairness: The model can produce toxic content, i.e., harmful, offensive, or detrimental to individuals, groups, or communities.
Transparency: Users are encouraged to perform their risk analysis on these models.
Accountability: Developers of TeenyTinyLlama
Mitigation Strategies: Hasn't been outlined specifically.
Input Output
Input Format: Uses special tokens to demarcate user queries and model responses.
Accepted Modalities:
Output Format: Generates text in response to queries.
Performance Tips: Ensure human moderation in interactive 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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