Qwen3 0.6B – Mental Health Fine-Tuned Model
Model Overview
Model Details
- Model Name:
adilthyl/Qwen3_0.6B_MentalHealth_FineTune - Base Model: Qwen3 0.6B
- Fine-tuned by: Adil Thayyil
- Version: v1.0
- Type: Decoder-only Transformer Language Model
- License: Apache 2.0 (confirm compatibility with base model license)
Intended Use
- Primary Use Case:
Provide empathetic, supportive, and informative responses in mental health conversations. - Domains:
Mental health support, wellness advice, stress management. - Scenarios:
- Conversational agents for emotional support
- Educational mental health tools
- Research in NLP for mental health dialogue
Important:
This model is not intended for commercial deployment.
It is provided for experimentation and educational purposes only.
Limitations
- Not a substitute for professional mental health care.
- May generate inaccurate or biased responses.
- Requires human oversight when used in sensitive contexts.
- Not intended for commercial deployment.
Ethical Considerations
- Safety: Trained with filters to minimize harmful outputs.
- Bias: May inherit biases present in the training data.
- Responsible Use:
Should not be used for diagnosis or medical treatment.
Intended solely for educational and experimental research.
How to Use
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "adilthyl/Qwen3_0.6B_MentalHealth_FineTune"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
inputs = tokenizer("I feel very anxious today, what should I do?", return_tensors="pt")
outputs = model.generate(**inputs, max_length=200)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))