app.py

from transformers import AutoTokenizer, T5ForConditionalGeneration
import gradio as gr

model_name = "SEBIS/code_trans_t5_base_code_comment_generation_java"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = T5ForConditionalGeneration.from_pretrained(model_name)

def generate_comment(code: str):
    inputs = tokenizer(code, return_tensors="pt")
    outputs = model.generate(**inputs, max_length=128)
    comment = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return comment

iface = gr.Interface(fn=generate_comment, inputs="text", outputs="text")
iface.launch()