Update sentiment-analyser.py

sentiment-analyser.py

@@ -3,7 +3,7 @@ from transformers import pipeline, AutoTokenizer
 
 st.title('Sentiment Analyser App')
 st.write('Welcome to my sentiment analysis app!')
-model_options=["sentiment-analysis", "twitter-xlm-roberta-base-sentiment"]
+model_options=["sentiment-analysis", "twitter-xlm-roberta-base-sentiment", "sentiment-roberta-large-english-3-classes"]
 
 form = st.form(key='sentiment-form')
 model_type = form.selectbox(label="Select a model", options=model_options)
@@ -16,6 +16,9 @@ def classification(user_input, type):
     elif type=="twitter-xlm-roberta-base-sentiment":
         path="cardiffnlp/twitter-xlm-roberta-base-sentiment"
         classifier = pipeline("sentiment-analysis", model=path, tokenizer=path)
+    elif type=="sentiment-roberta-large-english-3-classes":
+        path="j-hartmann/sentiment-roberta-large-english-3-classes"
+        classifier = pipeline("text-classification", model=path, return_all_scores=True)
     result = classifier(user_input)[0]
     return result
 
@@ -23,7 +26,7 @@ if submit:
     resultf = classification(user_input, model_type)
     label = resultf['label']
     score = resultf['score']
-    if (label == 'POSITIVE') or (label =='Positive'):
+    if (label == 'POSITIVE') or (label =='Positive') or (label =='positive'):
             st.success(f'{label} sentiment (score: {score})')
     else:
         st.error(f'{label} sentiment (score: {score})')