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from transformers import BertTokenizer, BertForSequenceClassification
import torch
import streamlit as st
tokenizer = BertTokenizer.from_pretrained(
"ashish-001/Bert-Amazon-review-sentiment-classifier")
model = BertForSequenceClassification.from_pretrained(
"ashish-001/Bert-Amazon-review-sentiment-classifier")
def classify_text(text):
inputs = tokenizer(
text,
max_length=256,
truncation=True,
padding="max_length",
return_tensors="pt"
)
output = model(**inputs)
logits = output.logits
probs = torch.nn.functional.sigmoid(logits)
return probs
st.title("Amazon Review Sentiment classifier")
data = st.text_area("Enter or paste a review")
if st.button('Predict'):
prediction = classify_text(data)
st.header(
f"{prediction}")
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