Model Type | text generation, transformers |
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Use Cases |
Areas: | Research, Commercial applications |
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Applications: | Assistant-like chat, Natural language generation tasks |
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Primary Use Cases: | Multilingual dialogue use cases |
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Limitations: | Use must comply with the Llama 3.1 Community License |
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Considerations: | Ensure any additional languages and use cases are safe and adhere to guidelines. |
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Additional Notes | Designed for openness, inclusivity, and helpfulness in various applications. |
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Supported Languages | English (High), German (High), French (High), Italian (High), Portuguese (High), Hindi (High), Spanish (High), Thai (High) |
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Training Details |
Data Sources: | 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: | |
Model Architecture: | Auto-regressive transformer architecture |
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Safety Evaluation |
Methodologies: | Fine-tuning data evaluation, Red teaming |
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Risk Categories: | |
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Responsible Ai Considerations |
Transparency: | Models developed following the best practices outlined in Responsible Use Guide. |
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Accountability: | Developers are expected to ensure safety by implementing internal safeguards. |
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Mitigation Strategies: | Safety fine-tuning and developing large language model classifiers. |
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Input Output |
Input Format: | ChatML prompt template, Alpaca prompt |
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Accepted Modalities: | |
Output Format: | Multilingual textual outputs |
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Performance Tips: | Use supported languages. Integrate safety guardrails in application setup. |
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Release Notes |
Version: | |
Date: | |
Notes: | This is a static model trained on an offline dataset with multilingual support and extended context length. |
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