Instructions to use help2opensource/Qwen3-4B-Instruct-2507_mental_health_therapy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use help2opensource/Qwen3-4B-Instruct-2507_mental_health_therapy with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-4B-Instruct-2507") model = PeftModel.from_pretrained(base_model, "help2opensource/Qwen3-4B-Instruct-2507_mental_health_therapy") - Transformers
How to use help2opensource/Qwen3-4B-Instruct-2507_mental_health_therapy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="help2opensource/Qwen3-4B-Instruct-2507_mental_health_therapy") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("help2opensource/Qwen3-4B-Instruct-2507_mental_health_therapy", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use help2opensource/Qwen3-4B-Instruct-2507_mental_health_therapy with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "help2opensource/Qwen3-4B-Instruct-2507_mental_health_therapy" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "help2opensource/Qwen3-4B-Instruct-2507_mental_health_therapy", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/help2opensource/Qwen3-4B-Instruct-2507_mental_health_therapy
- SGLang
How to use help2opensource/Qwen3-4B-Instruct-2507_mental_health_therapy with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "help2opensource/Qwen3-4B-Instruct-2507_mental_health_therapy" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "help2opensource/Qwen3-4B-Instruct-2507_mental_health_therapy", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "help2opensource/Qwen3-4B-Instruct-2507_mental_health_therapy" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "help2opensource/Qwen3-4B-Instruct-2507_mental_health_therapy", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use help2opensource/Qwen3-4B-Instruct-2507_mental_health_therapy with Docker Model Runner:
docker model run hf.co/help2opensource/Qwen3-4B-Instruct-2507_mental_health_therapy
Qwen3-4B-Instruct-2507_mental_health_therapy
Overview
This model is designed as a therapist assistant to support mental health professionals during client visits. It helps therapists engage with clients in a structured, empathetic way by facilitating emotional exploration, exploring concerns, and practicing active listening in a safe, non-judgmental environment.
The assistant supports real-time reflection and contextualization of client experiences, helping therapists prepare for and deepen their understanding of client narratives β always recognizing that it does not replace professional clinical judgment or therapeutic intervention.
Intended Use
- Supporting mental health professionals during client visits by providing real-time, empathetic guidance for emotional reflection and visitor engagement
- Facilitating structured, compassionate dialogue to help therapists explore visitor concerns, validate emotions, and practice active listening
- Assisting therapists in contextualizing visitor experiences through reflective, non-judgmental prompts that promote deeper understanding and therapeutic rapport
- Helping clinicians prepare for and navigate sensitive conversations in a way that respects client autonomy, dignity, and emotional well-being
Key Features
- Empathetic, non-judgmental responses
- Structured support for emotional exploration
- Safe space for discussing mental health concerns
- Designed to enhance user preparation for professional therapy sessions
Ethical & Safety Guidelines
β οΈ Important Limitations:
- β Cannot diagnose, assess, or provide medical advice
- β Cannot replace therapy, counseling, or crisis intervention
- β Should not be used during active crises (e.g., suicidal ideation, self-harm, psychosis)
- β Not intended as a substitute for a licensed mental health professional
π¨ Crisis Response Protocol:
If a user expresses suicidal thoughts, self-harm, or severe emotional distress β the model will:
- Acknowledge the seriousness of the situation
- Respond with empathy and concern
- Immediately prompt the user to contact a licensed therapist or emergency services
π‘ Safety Mechanisms:
- Automatic detection of crisis indicators (e.g., "I want to hurt myself", "I can't go on")
- Escalation to human support when needed
- All outputs are designed to prioritize user safety and well-being
Usage Notes
- Should be used in conjunction with, not instead of, professional therapy
- Not recommended for individuals experiencing active mental health crises
Disclaimer
This model is not a substitute for professional mental health care. It is intended to support emotional exploration and self-understanding in the context of therapy. Always seek help from a licensed therapist, counselor, or mental health professional when needed.
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Base model
Qwen/Qwen3-4B-Instruct-2507