Model Type | |
Use Cases |
Areas: | |
Applications: | Assistant-like chat, Natural language generation tasks |
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Primary Use Cases: | Dialogue, Instruction tuning |
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Limitations: | Must not violate the Acceptable Use Policy or applicable laws, Out-of-scope for languages other than English |
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Considerations: | Developers must comply with the Acceptable Use Policy and Community License. |
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Additional Notes | Open-sourced Purple Llama tools for community use and safety enhancement. |
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Supported Languages | English (Fully supported) |
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Training Details |
Data Sources: | A new mix of publicly available online data. |
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Data Volume: | |
Methodology: | Supervised Fine-Tuning (SFT), Reinforcement Learning with Human Feedback (RLHF) |
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Context Length: | |
Hardware Used: | |
Model Architecture: | Auto-regressive language model; uses Grouped-Query Attention (GQA) for improved inference scalability |
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Safety Evaluation |
Methodologies: | Red teaming, Adversarial evaluations |
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Findings: | Model significantly less likely to falsely refuse prompts |
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Risk Categories: | Misinformation, Cybersecurity, Child Safety |
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Ethical Considerations: | Responsible Use Guide updated for model and system-level safety. |
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Responsible Ai Considerations |
Fairness: | Designed to serve a diverse range of applications and respect free thought and expression. |
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Transparency: | Provided through open consortiums like AI Alliance and MLCommons. |
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Accountability: | Meta's sustainability program offsets all CO2 emissions. |
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Mitigation Strategies: | Integration with Purple Llama for additional safety measures. |
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Input Output |
Input Format: | |
Accepted Modalities: | |
Output Format: | |
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