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| import streamlit as st | |
| from transformers import AutoTokenizer , AutoModelForSequenceClassification | |
| import torch | |
| tokenizer = AutoTokenizer.from_pretrained('nlptown/bert-base-multilingual-uncased-sentiment') | |
| model = AutoModelForSequenceClassification.from_pretrained('nlptown/bert-base-multilingual-uncased-sentiment') | |
| st.set_page_config( | |
| page_title="NLP WEB APP" | |
| ) | |
| st.title("SENTIMENT ANALYZER") | |
| st.sidebar.success("Select a page above") | |
| message= st.text_input("ENTER THE MESSAGE") | |
| if st.button("PREDICT"): | |
| tokens = tokenizer.encode(message , return_tensors='pt') | |
| output = model(tokens) | |
| result = int(torch.argmax(output.logits))+1 | |
| if result==1: | |
| st.header("TOO MUCH NEGATIVE STATEMENT") | |
| st.header("RATING : ⭐ ") | |
| elif result==2: | |
| st.header("NEGATIVE STATEMENT") | |
| st.header("RATING : ⭐⭐") | |
| elif result==3: | |
| st.header("NEUTRAL STATEMENT") | |
| st.header("RATING : ⭐⭐⭐") | |
| elif result==4: | |
| st.header("POSITIVE STATEMENT") | |
| st.header("RATING : ⭐⭐⭐⭐ ") | |
| elif result==5: | |
| st.header("TOO MUCH POSITIVE STATEMENT") | |
| st.header("RATING : ⭐⭐⭐⭐⭐ ") | |