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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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+
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+ # Wellness-Mini: Mental Health Conversational AI
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+
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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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+ - Maintain clear AI identity as a Sentinet AI Systems creation
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+
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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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+
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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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+
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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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+
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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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+
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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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+
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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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+
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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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+
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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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+
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+ ## Creator
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+ This model was developed by Om Bhojane.
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+
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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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+ ```