README.md

metadata

language: en
tags:
  - mental-health
  - healthcare
  - conversational
  - wellness
  - SmolLM-135M
  - fine-tuned
license: mit
pipeline_tag: text-generation

Wellness-Mini: Mental Health Conversational AI

Model Description

Wellness-Mini is a fine-tuned version of SmolLM-135M, specifically adapted for mental health conversations and assessments. The model is designed to:

• Provide mental health assessments based on user conversations
• Identify potential indicators of ADHD and Bipolar disorder
• Analyze emotional indicators and stress levels

Base Model

• Original model: SmolLM-135M (HuggingFaceTB/SmolLM-135M)
• Architecture: Causal Language Model
• Size: 135M parameters

Training Data

The model was trained on a curated dataset including:

• Reddit posts from mental health communities (ADHD and Bipolar subreddits)
• Professional medical prescriptions and guidelines
• Identity training examples
• Emotional and behavioral indicators

Features

1. Mental Health Assessment

   • Primary condition identification
   • Additional symptom indicators
   • Emotional state analysis

2. Identity Awareness

   • Consistently identifies as a Sentinet AI Systems creation
   • Clear AI identity in responses

3. Clinical Indicators Analysis

   • Sentiment analysis
   • Anxiety levels
   • Stress indicators
   • Emotional valence

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer
Load model and tokenizer
model_name = "ombhojane/wellness-mini"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
Example usage
messages = [{"role": "user", "content": "Who created you?"}]
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(inputs, max_new_tokens=50)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)

Limitations

• This is an AI assistant and not a replacement for professional medical advice
• Should be used as a supplementary tool only
• May not be suitable for emergency situations
• Responses should be verified by healthcare professionals

Ethical Considerations

• The model should be used responsibly in mental health contexts
• User privacy and data protection should be prioritized
• Clear disclosure of AI nature in healthcare applications

Creator

This model was developed by Om Bhojane.

Citation

If you use this model in your research or application, please cite:

@misc{wellness-mini,
author = {Om Bhojane},
title = {Wellness-Mini: Mental Health Conversational AI},
year = {2024},
publisher = {HuggingFace},
journal = {HuggingFace Hub},
howpublished = {\url{https://huggingface.co/ombhojane/wellness-mini}}
}