Weyaxi/HelpSteer-filtered-neural-chat-7b-v3-1-7B
Weyaxi/HelpSteer-filtered-neural-chat-7b-v3-1-7B is a 7 billion parameter language model, created by Weyaxi, that merges Intel/neural-chat-7b-v3-1 with Weyaxi/HelpSteer-filtered-7B-Lora. This model is designed for general conversational AI tasks, leveraging its merged architecture to enhance response quality. It supports a context length of 8192 tokens, making it suitable for applications requiring moderate conversational depth.
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Overview
Weyaxi/HelpSteer-filtered-neural-chat-7b-v3-1-7B is a 7 billion parameter language model developed by Weyaxi. It is a composite model, formed by merging two distinct components: Intel/neural-chat-7b-v3-1 and Weyaxi/HelpSteer-filtered-7B-Lora. This integration aims to combine the strengths of both base models to deliver improved performance in conversational AI.
Key Capabilities
- Conversational AI: Optimized for generating human-like responses in dialogue-based interactions.
- Merged Architecture: Benefits from the combined features of its constituent models, potentially leading to enhanced coherence and relevance in outputs.
- Context Handling: Supports a context window of 8192 tokens, allowing for more extended and nuanced conversations.
Good For
- General Chatbots: Suitable for developing chatbots that require robust conversational abilities.
- Interactive Applications: Can be used in applications where engaging and context-aware text generation is crucial.
- Research and Development: Provides a base for further fine-tuning or experimentation in the domain of instruction-tuned language models.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.