updates

app.py

@@ -1,26 +1,29 @@
 import streamlit as st
 from transformers import pipeline
 from pysentimiento import create_analyzer
+from transformers import AutoTokenizer, TFAutoModelForSequenceClassification
 
-hate_speech_analyzer = create_analyzer(task="hate_speech", lang="es")
 
-pipe = pipeline(task="sentiment-analysis")
 st.title("Toxic Tweets Analyzer")
 image = "kanye_tweet.jpg"
 st.image(image, use_column_width=True)
 
-# create a dropdown to select the model
-model = st.selectbox("Select model", ["sentiment-analysis transformer", "finiteautomata/bertweet-base-sentiment-analysis"])
+
+#select model
+model_name = st.selectbox("Select model", ["distilbert-base-uncased-finetuned-sst-2-english", "finiteautomata/bertweet-base-sentiment-analysis"])
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = TFAutoModelForSequenceClassification.from_pretrained(model_name)
+clf = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
 
 #form
 with st.form("my_form"):
     submitted = st.form_submit_button("Analyze")
     tweet = st.text_area("enter tweet here:", value="i'm nice at ping pong")
     if submitted:
-        out = None
-        if model == "sentiment-analysis transformer":
-            out = pipe(tweet)
-        else:
-            out = hate_speech_analyzer.predict(tweet)
+        out = clf(tweet)
             
+        #loading bar
+        st.spinner(text="...")
+        st.success('Done!')
+        st.balloons()
         st.json(out)