vinoth322006/mindful-chat
The vinoth322006/mindful-chat model is a 7 billion parameter instruction-tuned causal language model developed by Vinoth P. It is fine-tuned from Llama-2-7B-Instruct and specialized for mental health conversations. With a context length of 4096 tokens, this model is designed to facilitate supportive and empathetic interactions in mental health counseling scenarios.
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Model Overview
The vinoth322006/mindful-chat is a 7 billion parameter language model developed by Vinoth P, fine-tuned from the llama-2-7B-Instruct architecture. Licensed under MIT, this model is specifically designed for applications requiring empathetic and supportive dialogue.
Key Capabilities
- Mental Health Conversation: The primary capability of this model is to engage in mental health-related conversations, providing responses suitable for counseling contexts.
- Instruction Following: As it is fine-tuned from an instruction-tuned base model, it is capable of following instructions to generate relevant conversational outputs.
Training Details
The model was fine-tuned using the Amod/mental_health_counseling_conversations dataset. This dataset focuses on conversational exchanges relevant to mental health support, enabling the model to learn appropriate responses and empathetic communication styles.
Good For
- Mental Health Support Applications: Ideal for chatbots or AI assistants aimed at providing initial support or conversational interfaces in mental health domains.
- Empathy-driven Dialogue Systems: Suitable for use cases where empathetic and understanding responses are crucial.
- Research in AI for Mental Wellness: Can serve as a base model for further research and development in AI-powered mental health interventions.