from transformers import pipeline import numpy as np import torch import transformers import json import pandas as pd from numpy.random import seed seed(1) import emoji import string import nltk from nltk.corpus import stopwords from nltk.stem import PorterStemmer # PorterStemmer LancasterStemmer from nltk.stem import WordNetLemmatizer import re stemmer = PorterStemmer() # uncomment this when run first time nltk.download('wordnet') nltk.download('omw-1.4') nltk.download('stopwords') lemmatizer = WordNetLemmatizer() stopwords = nltk.corpus.stopwords.words('english') import gradio as gr pipe = pipeline("text-classification", model="dsmsb/16class_12k_newtest1618_xlm_roberta_base_27nov_v2_8epoch") def classify(text): output = pipe(text,top_k = 2) return {"class": output} inputs = gr.inputs.Textbox(label="pdf link") outputs = gr.outputs.Textbox(label="OCR Text") demo = gr.Interface(fn=classify,inputs=inputs,outputs=outputs) demo.launch()