Weyaxi/OpenHermes-2.5-neural-chat-7b-v3-2-7B
Weyaxi/OpenHermes-2.5-neural-chat-7b-v3-2-7B is a 7 billion parameter language model created by Weyaxi, formed by merging teknium/OpenHermes-2.5-Mistral-7B and Intel/neural-chat-7b-v3-2 using the TIES merge method. This model leverages the strengths of its base models, offering a balanced performance across various benchmarks. It is designed for general-purpose conversational AI and instruction-following tasks, supporting a 4096-token context length.
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Model Overview
Weyaxi/OpenHermes-2.5-neural-chat-7b-v3-2-7B is a 7 billion parameter language model developed by Weyaxi. It is a product of a TIES merge between two prominent models: teknium/OpenHermes-2.5-Mistral-7B and Intel/neural-chat-7b-v3-2. This merging strategy aims to combine the distinct capabilities of its constituent models, with specific weights applied during the merge process.
Key Capabilities & Performance
This model demonstrates solid performance across a range of benchmarks, as evaluated on the Open LLM Leaderboard. Its average score is 68.71, with notable results including:
- HellaSwag (10-Shot): 84.11
- Winogrande (5-shot): 78.53
- AI2 Reasoning Challenge (25-Shot): 66.38
- MMLU (5-Shot): 62.84
- TruthfulQA (0-shot): 63.59
- GSM8k (5-shot): 56.79
Prompting and Quantization
The model supports various prompt templates, with ChatML (from OpenHermes-2.5-Mistral-7B) and the neural-chat-7b-v3-2 format being recommended. For optimized deployment, several quantized versions are available through TheBloke, including GPTQ, GGUF, and AWQ formats, making it suitable for resource-constrained environments.