| Model Type | | instruct, chatml, DPO, RLHF, gpt4 synthetic data, distillation, function calling, json mode |
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| Use Cases |
| Areas: | | research, commercial applications |
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| Applications: | | chatbots, instruction following, function calling |
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| Primary Use Cases: | | multi-turn chat dialogue, function calling, structured JSON responses |
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| Limitations: | | Complexity in function calling setup |
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| Considerations: | | Consider special tokens and role formats when setting up prompts. |
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| Additional Notes | | Quantized versions available using GGUF. |
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| Supported Languages | |
| Training Details |
| Data Sources: | |
| Data Volume: | |
| Methodology: | | Merged and further RLHF'ed version combining Hermes 2 Pro and Meta's Llama-3 Instruct |
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| Context Length: | |
| Training Time: | |
| Model Architecture: | | Hermes-2 ฮ is a merged model combining Hermes 2 Pro and Meta's Llama-3 Instruct. |
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| Input Output |
| Input Format: | | ChatML format with system and user roles defined |
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| Accepted Modalities: | |
| Output Format: | | Text responses, structured JSON |
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| Performance Tips: | | Utilize ChatML or the prompt structure for function calling for optimal engagement. |
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| Release Notes |
| Version: | |
| Date: | |
| Notes: | | Merged model of Hermes 2 Pro and Meta's Llama-3 with enhancements for instruct and chat applications. |
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