Spaces:
Runtime error
Runtime error
File size: 2,110 Bytes
8894bfe 966faf5 770cc5e 8894bfe |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 |
### Adapted from https://huggingface.co/spaces/valurank/News_Articles_Categorization
#importing the necessary libraries
import gradio as gr
import numpy as np
import pandas as pd
import re
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch
#Defining the labels of the models
labels = ["business", "science","health", "world", "sport", "politics", "entertainment", "tech"]
#Defining the models and tokenuzer
model_name = "valurank/finetuned-distilbert-news-article-categorization"
model = AutoModelForSequenceClassification.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)
"""
#Reading in the text file
def read_in_text(url):
with open(url, 'r') as file:
article = file.read()
return article
"""
def clean_text(raw_text):
text = raw_text.encode("ascii", errors="ignore").decode(
"ascii"
) # remove non-ascii, Chinese characters
text = re.sub(r"\n", " ", text)
text = re.sub(r"\n\n", " ", text)
text = re.sub(r"\t", " ", text)
text = text.strip(" ")
text = re.sub(
" +", " ", text
).strip() # get rid of multiple spaces and replace with a single
text = re.sub(r"Date\s\d{1,2}\/\d{1,2}\/\d{4}", "", text) #remove date
text = re.sub(r"\d{1,2}:\d{2}\s[A-Z]+\s[A-Z]+", "", text) #remove time
return text
#Defining a function to get the category of the news article
def get_category(text):
text = clean_text(text)
input_tensor = tokenizer.encode(text, return_tensors="pt", truncation=True)
logits = model(input_tensor).logits
softmax = torch.nn.Softmax(dim=1)
probs = softmax(logits)[0]
probs = probs.cpu().detach().numpy()
max_index = np.argmax(probs)
emotion = labels[max_index]
return emotion
#Creating the interface for the radio app
demo = gr.Interface(get_category,
inputs=gr.inputs.Textbox(label="Paste article text here",lines=4),
outputs = "text",
title="News Article Categorization")
#Launching the gradio app
if __name__ == "__main__":
demo.launch(debug=True) |