Create app.py

app.py

@@ -0,0 +1,14 @@
+import gradio as gr
+import torch
+from transformers import T5ForConditionalGeneration,AutoTokenizer,pipeline
+
+tokenizer = AutoTokenizer.from_pretrained('SeyedAli/Persian-Text-paraphraser-mT5-V1',model_max_length=100, add_special_tokens = True)
+model = T5ForConditionalGeneration.from_pretrained('SeyedAli/Persian-Text-paraphraser-mT5-V1')
+
+def NER(text):
+    pipline = pipeline(task='text2text-generation', model=model, tokenizer=tokenizer)
+    output=pipline(text)
+    return output
+
+iface = gr.Interface(fn=NER, inputs="text", outputs="text")
+iface.launch(share=False)