| Model Type | | text generation, question answering |
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| Use Cases |
| Areas: | | research, commercial applications |
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| Applications: | | chatbots, content creation |
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| Primary Use Cases: | | customer support, educational tools |
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| Limitations: | | Not suitable for medical advice, Struggles with ambiguous queries |
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| Considerations: | | Regularly update to latest version for best performance. |
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| Additional Notes | | Ensure to handle generated content ethically. |
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| Supported Languages | | English (fluent), Spanish (intermediate) |
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| Training Details |
| Data Sources: | |
| Data Volume: | |
| Methodology: | |
| Context Length: | |
| Training Time: | |
| Hardware Used: | |
| Model Architecture: | |
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| Safety Evaluation |
| Methodologies: | | red-teaming, unit testing |
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| Findings: | | low bias in gender roles, possible hallucinations |
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| Risk Categories: | |
| Ethical Considerations: | | Adheres to OpenAI's ethical AI guidelines. |
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| Responsible Ai Considerations |
| Fairness: | | Efforts to reduce gender and race bias in training data. |
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| Transparency: | | Core algorithm and data sources disclosed. |
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| Accountability: | | Developers are partially accountable for misuse. |
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| Mitigation Strategies: | | Regular updates and improvements. |
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| Input Output |
| Input Format: | |
| Accepted Modalities: | |
| Output Format: | | generated text, JSON format |
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| Performance Tips: | | Utilize batch processing for faster responses. |
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| Release Notes | |
