Model Type | |
Use Cases |
Areas: | |
Applications: | assistant-like chat, natural language generation tasks |
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Primary Use Cases: | optimized for dialogue use cases |
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Limitations: | Inaccurate, biased or other objectionable responses possible; testing primarily in English |
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Considerations: | Perform safety testing and tuning tailored to specific applications |
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Training Details |
Data Sources: | publicly available online data |
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Data Volume: | |
Methodology: | Supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) |
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Context Length: | |
Hardware Used: | Meta's Research Super Cluster, A100-80GB GPUs |
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Model Architecture: | Optimized transformer architecture |
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Input Output |
Input Format: | |
Accepted Modalities: | |
Output Format: | |
Performance Tips: | A specific formatting, including `INST`, `<>`, `BOS`, and `EOS` tokens, is required for optimal performance |
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