| 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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