app.py

from transformers import AutoTokenizer, AutoModelWithLMHead
import gradio as gr

tokenizer = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-emotion")
model = AutoModelWithLMHead.from_pretrained("mrm8488/t5-base-finetuned-emotion")
def get_emotion(text):
  input_ids = tokenizer.encode(text + '</s>', return_tensors='pt')
  output = model.generate(input_ids=input_ids,max_length=2)
  dec = [tokenizer.decode(ids) for ids in output]
  label = dec[0]
  return label.split()[1]

iface = gr.Interface(fn=get_emotion, inputs=["textbox"], outputs="text").launch()
iface