Model Type | text generation, code generation |
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Use Cases |
Areas: | |
Applications: | Dialogue use cases, Natural language generation |
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Primary Use Cases: | Assistant-like chat, Adaptation for various tasks |
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Limitations: | Use in non-English languages bypassing the license, Violation of laws or use policies |
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Considerations: | Developers can fine-tune for other languages following the license and use policy. |
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Additional Notes | In developing these models, the goal was to optimize for helpfulness and safety. Emphasis on community contributions for improving the Llama technology. |
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Supported Languages | |
Training Details |
Data Sources: | Publicly available online data |
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Data Volume: | |
Methodology: | Supervised fine-tuning and reinforcement learning with human feedback |
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Hardware Used: | Meta's Research SuperCluster, Third-party cloud compute |
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Model Architecture: | Auto-regressive language model with transformer architecture, tuned using SFT and RLHF. |
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Safety Evaluation |
Methodologies: | Red-teaming, Adversarial evaluations |
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Findings: | Residual risks remain, mitigations implemented |
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Risk Categories: | Cybersecurity, Child Safety |
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Ethical Considerations: | Developed considering responsible AI practices, with guides and resources provided to the community. |
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Responsible Ai Considerations |
Mitigation Strategies: | Llama Guard and Code Shield safeguards provided for safety mitigation. |
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Input Output |
Input Format: | |
Accepted Modalities: | |
Output Format: | |
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Release Notes |
Version: | |
Notes: | Meta released Llama 3 models optimized for helpfulness and safety in two sizes, 8B and 70B parameters. |
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