Update README.md

README.md

@@ -37,23 +37,19 @@ from transformers import AutoModelForSequenceClassification, AutoTokenizer
 import numpy as np
 from scipy.special import expit
 
-### Load the pre-trained model and tokenizer
 MODEL = "PavanDeepak/Topic_Classification"
 tokenizer = AutoTokenizer.from_pretrained(MODEL)
 model = AutoModelForSequenceClassification.from_pretrained(MODEL)
 class_mapping = model.config.id2label
 
-### Example text
 text = "I love chicken manchuria"
 tokens = tokenizer(text, return_tensors="pt")
 output = model(**tokens)
 
-### Get scores and predictions
 scores = output.logits[0][0].detach().numpy()
 scores = expit(scores)
 predictions = (scores >= 0.5) * 1
 
-### Print predicted labels
 for i in range(len(predictions)):
     if predictions[i]:
         print(class_mapping[i])