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| import streamlit as st | |
| import torch as nn | |
| import requests | |
| from transformers import pipeline | |
| ############ 1. PAGE LAYOUT, TITLE | |
| st.set_page_config( | |
| layout="centered", page_title='Simple Sentiment Analysis App Using\n\ | |
| Hugging Face Model Library', page_icon="(y)" | |
| ) | |
| c1,c2,c3 = st.columns([1,3,1]) | |
| with c1: | |
| st.write("") | |
| with c2: | |
| st.image("images/emotions.png") | |
| with c3: | |
| st.write("") | |
| # prepare a list of top sentiment analysis models including default | |
| models = ["distilbert-base-uncased-finetuned-sst-2-english",#default | |
| "bhadresh-savani/distilbert-base-uncased-emotion",#emotions | |
| "ProsusAI/finbert",#finance | |
| "finiteautomata/bertweet-base-sentiment-analysis",#tweets | |
| "cardiffnlp/twitter-roberta-base-sentiment"#tweet2 | |
| ] | |
| model_pointers = ["default: distilbert-base-uncased-finetuned-sst-2-english", | |
| "emotion: bhadresh-savani/distilbert-base-uncased-emotion", | |
| "finance: ProsusAI/finbert", | |
| "tweets: finiteautomata/bertweet-base-sentiment-analysis", | |
| "tweets2: cardiffnlp/twitter-roberta-base-sentiment" | |
| ] | |
| #Prompt User for input text for sentiment analysis, keep input and model selection in form to delay page refresh | |
| with st.form(key="init_form"): | |
| input_text = st.text_area("Input a sentence on which to perform sentiment\ | |
| analysis", value="I love Streamlit and I love Data Science!") | |
| choice = st.selectbox("Choose Model", model_pointers) | |
| # The index of choice in model_pointers will access the models list | |
| # and select the Hugging Face model path at index. | |
| user_picked_model = models[model_pointers.index(choice)] | |
| with st.spinner("Downloading Model"): | |
| sentiment_pipeline = pipeline(model=user_picked_model) | |
| analyze = st.form_submit_button("Analyze") | |
| if analyze: | |
| with st.spinner("Analyzing..."): | |
| sentiment_pipeline = pipeline(model=user_picked_model) | |
| sentiment_results=sentiment_pipeline(input_text) | |
| st.write(f"Sentiment: {sentiment_results[0]['label']}") | |
| st.write(f"Score: {sentiment_results[0]['score']}") | |
| else: | |
| st.write("no input detected") | |