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This model is a fine-tuned version of the Llama 2 model ("NousResearch/Llama-2-7b-chat-hf") using a personalized dataset for a virtual therapy chatbot. The model is designed to assist users in providing mental health support through conversations that mimic real-world therapy interactions.

Model Details

Model Description

TThis model is a fine-tuned version of the Llama 2 base model, specifically designed for a chatbot to assist in virtual therapy and mental health counseling. It has been fine-tuned with a dataset of responses from real-world therapy interactions, focusing on providing personalized, empathetic replies. The model is trained using the Quantized Low-Rank Adaptation (QLoRA) technique for efficient fine-tuning.

  • Developed by: [More Information Needed]
  • Model type: LLM
  • Language(s) : NLP
  • Finetuned from model [optional]: NousResearch/Llama-2-7b-chat-hf

Model Sources [optional]

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Uses

The model is intended to be used as a virtual mental health support tool. It provides personalized, context-aware responses for individuals seeking help with issues such as anxiety, stress, relationships, and personal growth.

Direct Use

The model can be used for chatbot applications where users engage in conversations seeking therapeutic or emotional support. It is especially suited for mental health contexts where empathy and personalization are key.

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Downstream Use [optional]

The model can be fine-tuned further for specific mental health tasks, such as Cognitive Behavioral Therapy (CBT) or mindfulness coaching. It could also be integrated into apps or services where mental health support is needed.

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Out-of-Scope Use

The model should not be used for making medical diagnoses or providing crisis intervention support. It is not designed to replace professional therapy and is intended as a support tool, not a primary care option.

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Bias, Risks, and Limitations

This model, like any AI-based therapy chatbot, has limitations. It might not always fully understand the context of user conversations, and there may be biases based on the training data. The model also has limitations in dealing with complex or crisis situations.

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Recommendations

Users of the model should ensure that it is clear to end-users that the chatbot is not a substitute for professional mental health care. Monitoring for sensitive or high-risk conversations is recommended, and appropriate actions should be taken when the model encounters issues beyond its scope.

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

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Training Details

Training Data

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Training Procedure

Preprocessing [optional]

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Training Hyperparameters

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Speeds, Sizes, Times [optional]

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Evaluation

Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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Summary

Model Examination [optional]

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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Citation [optional]

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