app.py

import gradio as gr
from gradio.mix import Parallel, Series
from transformers import SegformerFeatureExtractor, SegformerForImageClassification
from PIL import Image
import requests

feature_extractor = SegformerFeatureExtractor.from_pretrained("nvidia/mit-b0")
model = SegformerForImageClassification.from_pretrained("nvidia/mit-b0")

description = "BigGAN text-to-image demo."
title = "BigGAN ImageNet"

Gans=["biggan-deep-128", "biggan-deep-256", "biggan-deep-512"]

io1 = gr.Interface.load('huggingface/osanseviero/BigGAN-deep-128')
io2 = gr.Interface.load("huggingface/osanseviero/BigGAN-deep-128")
io3 = gr.Interface.load(model)                  
#io3 = gr.Interface.load("huggingface/emilyalsentzer/Bio_Discharge_Summary_BERT")                  
#io3 = gr.Interface.load("huggingface/google/pegasus-pubmed")  
#io3 = gr.Interface.load("huggingface/tennessejoyce/titlewave-t5-base")  

# = Parallel(io1, io2, io3,

interface = Parallel(io1,io2,io3, 
            description=description,
            title = title,
            examples=[
            ["lighthouse"],
            ["eyeglasses"],
            ["stool"],
            ["window"],
            ["hand"],
            ["dice"],
            ["cloud"],
            ["gate"],
            ["cat"],
            ["toes"]
            ]
)
interface.launch()