| Model Type | | text-generation, multilingual | 
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| Use Cases | 
| Areas: |  |  | Applications: | | assistant-like chat, natural language generation tasks, synthetic data generation | 
 |  | Primary Use Cases: |  |  | Limitations: | | not for use beyond 8 supported languages without fine-tuning and compliance with terms | 
 |  | Considerations: | | ensure safety in additional languages | 
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| Additional Notes | | Used for commercial and research purposes. Regular updates to improve model safety with community feedback. | 
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| Supported Languages | | English (full), German (full), French (full), Italian (full), Portuguese (full), Hindi (full), Spanish (full), Thai (full) | 
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| Training Details | 
| Data Sources: | | publicly available online data | 
 |  | Data Volume: |  |  | Methodology: | | supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) | 
 |  | Context Length: |  |  | Training Time: |  |  | Hardware Used: | | custom built GPU cluster, H100-80GB | 
 |  | Model Architecture: | | optimized transformer architecture | 
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| Safety Evaluation | 
| Methodologies: | | red teaming, risk assessments, evaluation datasets | 
 |  | Findings: | | some safety risks identified and mitigated | 
 |  | Risk Categories: | | misinformation, cyber threats, child safety | 
 |  | Ethical Considerations: | | engagement strategies with subject-matter experts for real-world harms | 
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| Responsible Ai Considerations | 
| Fairness: | | efforts to mitigate bias through multi-faceted data collection approach | 
 |  | Transparency: | | part of an open community for AI safety progress | 
 |  | Accountability: | | use of output reporting mechanism | 
 |  | Mitigation Strategies: | | adopting MLCommons taxonomy, employing numerous safety guardrails | 
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| Input Output | 
| Input Format: |  |  | Accepted Modalities: |  |  | Output Format: | | multilingual text and code | 
 |  | Performance Tips: | | Follow the Responsible Use Guide | 
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| Release Notes | | 
| Version: |  |  | Date: |  |  | Notes: | | Enhancements for multilingual dialogue, improved benchmarks results. | 
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