flemmingmiguel/Distilled-HermesChat-7B
flemmingmiguel/Distilled-HermesChat-7B is a 7 billion parameter language model created by flemmingmiguel, formed by merging openchat/openchat-3.5-0106 and argilla/distilabeled-Hermes-2.5-Mistral-7B. This model is an experimental merge designed to identify optimal base configurations for further fine-tuning. It leverages a slerp merge method with specific parameter adjustments for self-attention and MLP layers, making it suitable for general conversational AI tasks and as a foundation for specialized applications.
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Overview
Distilled-HermesChat-7B is an experimental 7 billion parameter language model developed by flemmingmiguel. It is constructed through a merge of two distinct models: openchat/openchat-3.5-0106 and argilla/distilabeled-Hermes-2.5-Mistral-7B. The primary goal of this merge is to explore and identify the most effective base model combination for subsequent fine-tuning efforts.
Key Characteristics
- Architecture: A merged model combining elements from OpenChat and Hermes 2.5 Mistral-7B.
- Merge Method: Utilizes the
slerp(spherical linear interpolation) merge method, with specifictparameter adjustments applied to self-attention and MLP layers to balance contributions from the source models. - Experimental Nature: Positioned as an experiment to benchmark and determine a strong foundational merge for further development.
Good For
- General Conversational AI: Suitable for a wide range of chat-based applications due to its lineage from instruction-tuned models.
- Base for Fine-tuning: Designed as a robust starting point for developers looking to fine-tune a model for specific tasks or domains.
- Research and Experimentation: Ideal for researchers interested in model merging techniques and their impact on performance.