app.py

import gradio as gr
from transformers import T5ForConditionalGeneration, RobertaTokenizer

# Load the quantized model and tokenizer from Hugging Face Hub
quantized_model = T5ForConditionalGeneration.from_pretrained("AbdulHadi806/codet5-finetuned-latest-quantized")
tokenizer = RobertaTokenizer.from_pretrained("AbdulHadi806/codet5-finetuned-latest-quantized")

def inference(input_text):
    inputs = tokenizer(input_text, return_tensors="pt")
    outputs = quantized_model.generate(**inputs)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

# Create Gradio interface
iface = gr.Interface(fn=inference, inputs="text", outputs="text")

# Launch the interface
iface.launch()