app.py

import gradio as gr
from transformers import AutoModelForSequenceClassification
from transformers import AutoTokenizer
from transformers import pipeline

model_loader = AutoModelForSequenceClassification.from_pretrained("content/models")
tokenizer_loader = AutoTokenizer.from_pretrained("content/models")
model_loader.eval()
print("loaded")

classifier = pipeline("sentiment-analysis", model=model_loader, tokenizer=tokenizer_loader, device=0)


def greet(twitter):
    pred = classifier(twitter)[0]
    return "twitter is %s with score=%.4f" % (pred['label'], pred['score'])


if __name__ == '__main__':
    interFace = gr.Interface(fn=greet, inputs="text", outputs="text")
    interFace.launch()