| 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 Paraphrase(text): | |
| pipline = pipeline(task='text2text-generation', model=model, tokenizer=tokenizer) | |
| output=pipline(text) | |
| return output | |
| iface = gr.Interface(fn=Paraphrase, inputs="text", outputs="text") | |
| iface.launch(share=False) |