XformAI-india/qwen-0.6b-mentalhealth-support

🧠 Qwen-0.6B Mental Health Support (Fine-Tuned)

Model Repo: xformai/qwen-0.6b-mentalhealth-support Base Model: `Qwen/Qwen-0.5B` Task: Empathetic Conversational AI for mental health & emotional support Fine-Tuned By: XformAI

🧠 What is this?

This is a fine-tuned version of the Qwen-0.6B language model, adapted on a curated dataset focused on mental health support and empathetic responses. The goal is to enable helpful, emotionally aware, and safe conversations around stress, anxiety, depression, and general wellness.

🧪 Use Cases

• —Mental health chatbots
• —Emotional support agents
• —Wellness coaching prototypes
• —Journaling assistants

📊 Training Details

• —Dataset: Internal collection of therapy-style dialogues, emotional support threads, and curated mental health Q&A (non-clinical)
• —Epochs: 3
• —Batch Size: 16
• —Optimizer: AdamW
• —Context Window: 2048
• —Precision: bfloat16
• —Framework: Hugging Face Transformers + PEFT (LoRA)

🚨 Warnings

⚠️ This model is not a substitute for professional medical or mental health advice. It is trained to offer support-style language, not diagnosis or clinical recommendations.

🧠 Example Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("xformai/qwen-0.6b-mentalhealth-support")
tokenizer = AutoTokenizer.from_pretrained("xformai/qwen-0.6b-mentalhealth-support")

prompt = "I've been feeling really overwhelmed lately. Can you help?"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))