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--- |
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language: en |
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tags: |
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- mental-health |
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- healthcare |
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- conversational |
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- wellness |
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- SmolLM-135M |
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- fine-tuned |
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license: mit |
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pipeline_tag: text-generation |
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--- |
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# Wellness-Mini: Mental Health Conversational AI |
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## Model Description |
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Wellness-Mini is a fine-tuned version of SmolLM-135M, specifically adapted for mental health conversations and assessments. The model is designed to: |
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- Provide mental health assessments based on user conversations |
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- Identify potential indicators of ADHD and Bipolar disorder |
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- Analyze emotional indicators and stress levels |
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## Base Model |
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- Original model: SmolLM-135M (HuggingFaceTB/SmolLM-135M) |
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- Architecture: Causal Language Model |
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- Size: 135M parameters |
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## Training Data |
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The model was trained on a curated dataset including: |
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- Reddit posts from mental health communities (ADHD and Bipolar subreddits) |
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- Professional medical prescriptions and guidelines |
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- Identity training examples |
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- Emotional and behavioral indicators |
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## Features |
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1. **Mental Health Assessment** |
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- Primary condition identification |
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- Additional symptom indicators |
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- Emotional state analysis |
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2. **Identity Awareness** |
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- Consistently identifies as a Sentinet AI Systems creation |
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- Clear AI identity in responses |
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3. **Clinical Indicators Analysis** |
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- Sentiment analysis |
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- Anxiety levels |
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- Stress indicators |
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- Emotional valence |
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## Usage |
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``` python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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Load model and tokenizer |
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model_name = "ombhojane/wellness-mini" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForCausalLM.from_pretrained(model_name) |
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Example usage |
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messages = [{"role": "user", "content": "Who created you?"}] |
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
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inputs = tokenizer(prompt, return_tensors="pt") |
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outputs = model.generate(inputs, max_new_tokens=50) |
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response = tokenizer.decode(outputs[0], skip_special_tokens=True) |
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``` |
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## Limitations |
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- This is an AI assistant and not a replacement for professional medical advice |
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- Should be used as a supplementary tool only |
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- May not be suitable for emergency situations |
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- Responses should be verified by healthcare professionals |
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## Ethical Considerations |
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- The model should be used responsibly in mental health contexts |
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- User privacy and data protection should be prioritized |
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- Clear disclosure of AI nature in healthcare applications |
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## Creator |
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This model was developed by Om Bhojane. |
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## Citation |
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If you use this model in your research or application, please cite: |
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``` |
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@misc{wellness-mini, |
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author = {Om Bhojane}, |
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title = {Wellness-Mini: Mental Health Conversational AI}, |
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year = {2024}, |
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publisher = {HuggingFace}, |
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journal = {HuggingFace Hub}, |
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howpublished = {\url{https://huggingface.co/ombhojane/wellness-mini}} |
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} |
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``` |
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