Kquant03/Hippolyta-7B-bf16
Kquant03/Hippolyta-7B-bf16 is a 7 billion parameter language model fine-tuned by Kquant03 and ConvexAI, based on the Mistral-7B-v0.1 architecture with an 8192 token context length. This model was developed by reformatting various datasets and incorporating private data to enhance Mistral's capabilities. It is designed to improve upon the base Mistral model's performance, particularly in conversational and instruction-following tasks using the Mistral chat-instruct template.
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Overview
Kquant03/Hippolyta-7B-bf16 is a 7 billion parameter model developed by Kquant03 and ConvexAI, built upon the robust mistralai/Mistral-7B-v0.1 foundation. The development involved reformatting diverse public datasets and integrating a proprietary private dataset to specifically enhance the base Mistral model's performance. The model maintains an 8192 token context length, consistent with its base architecture.
Key Capabilities
- Enhanced Instruction Following: Fine-tuned with a focus on improving conversational and instruction-based interactions.
- Mistral Prompt Template: Utilizes the standard Mistral prompt template, specifically designed for chat-instruct applications.
- Dataset Reformatting: Benefits from a unique training approach involving the reformatting of multiple datasets, alongside private data, to optimize its responses.
Good For
- Conversational AI: Ideal for applications requiring engaging and coherent dialogue generation.
- Instruction-Based Tasks: Suitable for scenarios where the model needs to accurately follow specific instructions or prompts.
- Experimentation with Fine-tuned Mistral: Offers a refined version of Mistral-7B-v0.1 for developers looking for improved performance in specific areas.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.