Llama-2-7b-chat-hf-customMHByash

Model Card for Mental Health Chatbot (LoRA LLaMA-2-7B)

Model Description

This model is a LoRA fine-tuned version of meta-llama/Llama-2-7b-chat-hf, designed to act as a supportive conversational assistant for mental health–related discussions.

The model was trained using Supervised Fine-Tuning (SFT) on publicly available mental health conversation datasets to improve empathy, conversational flow, and instruction-following behavior.
This project was developed strictly for academic and research purposes.

⚠️ This model is not a licensed medical professional and must not be used as a replacement for professional mental health care.

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Model Details

• Developed by: Yash
• Funded by: Not funded (academic project)
• Shared by: Yash
• Model type: Large Language Model (LLM), conversational text generation
• Language(s): English
• License: LLaMA 2 Community License Agreement
• Finetuned from model: meta-llama/Llama-2-7b-chat-hf

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Model Sources

• Base Model Repository: meta-llama/Llama-2-7b-chat-hf
• Demo: Not provided
• Paper: Not applicable

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Uses

Direct Use

• Academic research on conversational AI
• Experimental mental health support chatbots
• Studying empathetic response generation
• NLP coursework and projects

Downstream Use

• Further fine-tuning for domain-specific assistants
• Integration into research prototypes with human oversight
• Evaluation of conversational safety techniques

Out-of-Scope Use

❌ Medical diagnosis
❌ Therapy or psychiatric treatment
❌ Crisis intervention or suicide prevention
❌ Any real-world deployment without professional supervision

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Bias, Risks, and Limitations

• The model may generate inaccurate or incomplete information
• Responses may reflect biases present in training data
• The model cannot assess real mental health conditions
• Risk of over-reliance if used without disclaimers
• Not trained for emergency or crisis scenarios

Recommendations

• Always include clear disclaimers when using this model
• Use with human moderation
• Do not deploy in clinical or high-risk environments
• Encourage users to seek professional help when appropriate

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How to Get Started with the Model

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base_model = "meta-llama/Llama-2-7b-chat-hf"
adapter_model = "your-username/your-model-name"

tokenizer = AutoTokenizer.from_pretrained(base_model)
model = AutoModelForCausalLM.from_pretrained(
    base_model,
    device_map="auto"
)

model = PeftModel.from_pretrained(model, adapter_model)
model.eval()