app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel

# Load the model and tokenizer from Hugging Face Model Hub
tokenizer = AutoTokenizer.from_pretrained("hariom329/Fashionista")
model = AutoModelForCausalLM.from_pretrained("hariom329/Fashionista")
model = PeftModel.from_pretrained(model, "hariom329/Fashionista")

def answer(query):
    inputs = tokenizer(query, return_tensors="pt")
    outputs = model.generate(**inputs, max_new_tokens=200)
    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return response

# Define the Gradio interface
iface = gr.Interface(fn=answer, inputs="text", outputs="text", title="Fashion Assistant")
iface.launch()