Kaneki24/llama3-1b-mental-health-chatbot

🧠 LLaMA3-1B Mental Health Chatbot

This model is a fine-tuned version of meta-llama/Llama-3.2-1B-Instruct using PEFT (Parameter-Efficient Fine-Tuning) for the specific task of providing empathetic and context-aware responses in the domain of mental health support.

📝 Model Details

🔧 Fine-Tuning

• —Base model: Llama-3.2-1B-Instruct by Meta
• —Fine-tuning method: LoRA (Low-Rank Adaptation) via PEFT
• —Dataset used: counselchat_llama_dataset.jsonl(Kaggle),Reddit_conv
• —Trained for: Providing guidance, emotional support, and safe responses in mental health scenarios.

💡 Intended Use

This model is designed to:

• —Assist users with emotional wellness questions
• —Respond with empathy and psychological safety
• —Provide general mental health tips and guidance

⚠️ Disclaimer: This model is not a substitute for professional medical or psychological help.

💻 How to Use

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-1B-Instruct", device_map="auto")
model = PeftModel.from_pretrained(base_model, "Kaneki24/llama3-1b-mental-health-chatbot")

tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.2-1B-Instruct")

prompt = "I'm feeling very anxious lately. Can you help?"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))