Model Type | text generation, multilingual |
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Use Cases |
Areas: | |
Applications: | Assistant-like chat, Natural language generation, Synthetic data generation |
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Primary Use Cases: | Multilingual dialogue, Instruction tuning |
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Limitations: | Usage in unsupported languages, Under circumstances violating applicable laws |
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Considerations: | Appropriate safeguards and responsible usage. |
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Additional Notes | Encouraged for research and commercial applications with responsibility and adherence to guidelines. |
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Supported Languages | English (Supported), German (Supported), French (Supported), Italian (Supported), Portuguese (Supported), Hindi (Supported), Spanish (Supported), Thai (Supported) |
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Training Details |
Data Sources: | publicly available sources, synthetically generated examples |
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Data Volume: | |
Methodology: | Auto-regressive transformer with supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) |
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Context Length: | |
Training Time: | |
Hardware Used: | |
Model Architecture: | Auto-regressive transformer |
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Safety Evaluation |
Methodologies: | Safety fine-tuning, Adversarial testing, Red-teaming |
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Risk Categories: | CBRNE helpfulness, Child Safety, Cyber attack enablement |
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Ethical Considerations: | Ensuring safe and responsible use. |
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Responsible Ai Considerations |
Fairness: | Emphasis on non-discrimination and safe engagement across languages. |
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Transparency: | Information on methodology and safety evaluations are shared. |
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Accountability: | Meta holds responsibility with guidelines for safe integration. |
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Mitigation Strategies: | Safety guardrails and community guidelines. |
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Input Output |
Accepted Modalities: | |
Output Format: | Multilingual Text and code |
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Performance Tips: | Ensure use of safeguards and compliance with guidelines. |
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Release Notes |
Version: | |
Date: | |
Notes: | Release of multilingual large models with improved tuning for safety and performance. |
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