app.py

import streamlit as st
from transformers import pipeline
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("openai/whisper-large")
model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-large")



pipe = pipeline('sentiment-analysis')
pipe2 =  pipeline(task="image-bestify", model="beihai/GFPGAN-V1.3-whole-image")
text = st.text_area('entre com algum texto')
st.title("Hot Dog? Or Not? ")
file_name = st.file_uploader("Upload a hot dog candidate image")
if text:
 out=pipe(text)
 st.json(out)