| Model Type | | Chat model, Text generation | 
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| Use Cases | 
| Areas: | | Chat applications, Creative content generation | 
 |  | Applications: | | Commercial applications, Research, Educational tools | 
 |  | Primary Use Cases: | | Chatbots, Virtual assistants, Story generation | 
 |  | Limitations: | | Potential for hallucination, May produce inconsistent outputs | 
 |  | Considerations: | | Adjust generation parameters for desired output qualities. | 
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| Additional Notes | | Models do not directly use Llama's weights; unique datasets and training infrastructure emphasize Yi's independent development. | 
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| Supported Languages | | English (Fluent), Chinese (Fluent) | 
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| Training Details | 
| Data Sources: | | Trainer Multilingual Corpora, 3T Tokens | 
 |  | Data Volume: |  |  | Methodology: | | Transformer-based architecture | 
 |  | Context Length: |  |  | Training Time: |  |  | Hardware Used: | | NVIDIA A800 (80GB), 4090 GPU | 
 |  | Model Architecture: | | Based on Llama's architecture | 
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| Responsible Ai Considerations | 
| Fairness: | | Addressed during model development. | 
 |  | Transparency: | | Standard Transformer architecture; detailed in tech report. | 
 |  | Accountability: |  |  | Mitigation Strategies: | | Use of Supervised Fine-Tuning for better accuracy. | 
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| Input Output | 
| Input Format: | | Interactive prompt conversation | 
 |  | Accepted Modalities: |  |  | Output Format: | | Text responses or follow-ups | 
 |  | Performance Tips: | | Calibrate temperature, top_p, top_k settings for desired response diversity. | 
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| Release Notes | | 
| Version: |  |  | Date: |  |  | Notes: | | Initial open-source release of chat model, supporting both 4-bit and 8-bit quantizations. | 
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| Version: |  |  | Date: |  |  | Notes: | | Improved performance in coding, math, and reasoning with larger context capabilities. | 
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