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import streamlit as st
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from transformers import DistilBertTokenizer, DistilBertForSequenceClassification
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import torch
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st.title("Multi classification Fine tunning model")
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model_dir = "distilbert_fine_tuned_model"
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tokenizer = DistilBertTokenizer.from_pretrained(model_dir)
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model = DistilBertForSequenceClassification.from_pretrained(model_dir)
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def predict_class(text):
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inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True, max_length=512)
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outputs = model(**inputs)
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prediction_value = torch.argmax(outputs.logits, dim=1).item()
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stars=[" 1 stars"," 2 stars"," 3 stars"," 4 stars"," 5 stars"]
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st.write(stars[prediction_value])
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inputs_text=st.text_input("Please enter the text",value="I think I really like this place. Ayesha and I had a chance to visit Cheuvront on a Monday night. It wasn\'t terribly busy when we arrived and we were warmly greeted. Unfortunately we were seated next to a loud group of young children that thought they knew something of the world ")
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if st.button("submit"):
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predict_class(inputs_text)
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