Model Type | multilingual large language model, generative |
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Use Cases |
Areas: | |
Applications: | multilingual dialogue systems |
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Primary Use Cases: | |
Limitations: | Prohibited uses as described in Acceptable Use Policy and License |
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Considerations: | Focuses on common industry benchmarks and safety guidelines. |
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Supported Languages | en (English), de (German), fr (French), it (Italian), pt (Portuguese), hi (Hindi), es (Spanish), th (Thai) |
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Training Details |
Data Sources: | publicly available online data |
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Data Volume: | |
Methodology: | Pretrained and instruction-tuned using SFT and RLHF |
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Context Length: | |
Training Time: | |
Hardware Used: | |
Model Architecture: | Optimized transformer architecture |
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Safety Evaluation |
Methodologies: | red teaming, adversarial testing |
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Risk Categories: | CBRNE (Chemical, Biological, Radiological, Nuclear, and Explosive materials), Child Safety, Cyber attack enablement |
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Ethical Considerations: | Potential societal impact and misuse prevention measures. |
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Responsible Ai Considerations |
Fairness: | Commitment to inclusivity and openness. |
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Transparency: | Providing thorough documentation and usage guidelines. |
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Accountability: | Meta and developers share responsibilities based on deployment. |
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Mitigation Strategies: | Introduction of safety guardrails like Llama Guard 3. |
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Input Output |
Input Format: | |
Accepted Modalities: | |
Output Format: | Multilingual Text and code |
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Release Notes |
Version: | |
Date: | |
Notes: | Multilingual model optimized for dialogue. |
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