| Model Type | | Text Generation, Multimodal |
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| Use Cases |
| Areas: | | Personal, Academic, Commercial |
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| Applications: | | Code generation, Math solutions, Commonsense reasoning, Reading comprehension |
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| Limitations: | | Hallucination potential, Non-determinism in response generation, Cumulative error in extended tasks |
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| Considerations: | | Adjust generation configuration parameters such as temperature, top_p, or top_k to improve output consistency. |
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| Supported Languages | |
| Training Details |
| Data Sources: | |
| Model Architecture: | | Transformer and Llama architectures |
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| Input Output |
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| Performance Tips: | | Recommendations to adjust temperature, top_p, or top_k settings for better output. |
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| Release Notes |
| Version: | |
| Date: | |
| Notes: | | Initial open-source release of Yi-34B and Yi-6B base models. |
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| Version: | |
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| Notes: | | Yi-9B becomes the top performer among similar-sized open-source models in coding, math, and reasoning. |
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