Create app.py

app.py

@@ -0,0 +1,15 @@
+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()