| Model Type | |
| Use Cases |
| Areas: | | Research, Commercial applications |
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| Primary Use Cases: | | Assistant-like chat, Natural language generation tasks |
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| Limitations: | | Use in languages other than English, Use violating laws or regulations, Use prohibited by Acceptable Use Policy |
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| Considerations: | | Safety testing tailored to specific applications is required. |
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| Additional Notes | | Models are trained with a global batch-size equivalent to 4M tokens and do not include Meta user data. |
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| Supported Languages | |
| Training Details |
| Data Sources: | | Open-Orca/OpenOrca-Platypus2-13B, WizardLM/WizardLM-13B-V1.2, 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, Third-party cloud compute |
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| Model Architecture: | | Auto-regressive language model with optimized transformer architecture |
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| Safety Evaluation |
| Methodologies: | | Internal evaluations, Safety benchmarks |
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| Findings: | | May produce inaccurate or biased responses, Potential outputs cannot be predicted in advance |
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| Risk Categories: | |
| Ethical Considerations: | | Responsible Use Guide available |
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| Responsible Ai Considerations |
| Fairness: | | Testing has been conducted primarily in English. |
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| Transparency: | | Limited transparency as outputs cannot be predicted. |
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| Accountability: | | Meta is accountable for model development. |
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| Mitigation Strategies: | | Safety testing and tuning guidelines provided in Responsible Use Guide. |
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| Input Output |
| Input Format: | | Alpaca instruction format |
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| Accepted Modalities: | |
| Output Format: | |
| Performance Tips: | | Use of specific formatting like `INST`, `<>`, `BOS`, `EOS` tokens, and attention to whitespace. |
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| Release Notes |
| Version: | |
| Notes: | | A merge of Open-Orca/OpenOrca-Platypus2-13B and WizardLM/WizardLM-13B-V1.2. |
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