Qwen2.5-3B Mental Health Item Generation (LoRA)
This repository contains a LoRA adapter fine-tuned on true/false mental health questionnaire item generation, with a focus on depression and anxiety dimensions.
⚠️ This repository only contains LoRA adapter weights.
You must load it together with the base model:
Qwen/Qwen2.5-3B-Instruct.
How to Use
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
base_model = AutoModelForCausalLM.from_pretrained(
"Qwen/Qwen2.5-3B-Instruct",
device_map="auto",
torch_dtype="auto",
trust_remote_code=True
)
model = PeftModel.from_pretrained(
base_model,
"Joshua0522/qwen25-3b-mental-health-itemgen-lora"
)
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-3B-Instruct")
prompt = """
Generate exactly 5 true/false depression questionnaire items.
"""
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))
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