debugging 3

app.py

@@ -10,13 +10,19 @@ st.title("Sentiment Analysis")
 def analyze(input, model):
     return "This is a sample output"
 
-
 # load my fine-tuned model
 fine_tuned = "jbraha/tweet-bert"
 labels = {'LABEL_0': 'toxic', 'LABEL_1': 'severe_toxic', 'LABEL_2': 'obscene', 'LABEL_3': 'threat',
           'LABEL_4': 'insult', 'LABEL_5': 'identity_hate'}
 
-# make a dictionary of the labels with keys like "LABEL_0" and values like "toxic"
+
+# make a dictionary of the labels and values
+def unpack(result):
+    output = {}
+    for res in result:
+        output[labels[res['label']]] = res['score']
+    return output
+
 
 #text insert
 input = st.text_area("Insert text to be analyzed", value="Nice to see you today.", 
@@ -32,25 +38,21 @@ option = st.selectbox(
 if option == 'Fine-Tuned':
     model = AutoModelForSequenceClassification.from_pretrained(fine_tuned)
     tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
-    classifier = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer)
+    classifier = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer, top_k=None)
 elif option == 'Roberta':
     model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
     tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
-    classifier = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer, top_k=None)
+    classifier = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer)
 else:
     classifier = pipeline('sentiment-analysis')
 
 
 if st.button('Analyze'):
     result = classifier(input)
-    print(result)
-    print(type(result))
     output = None
     result = result[0]
     if option == 'Fine-Tuned':
-        output = {'Toxic': result['LABEL_0']}
-        del result['LABEL_0']
-        output[max(result, key=result.get)] = result[max(result, key=result.get)]
+        output = unpack(result)
     else:
         output = result
     st.write(output)
@@ -60,3 +62,5 @@ else:
 
 
 
+
+