testing dup

app.py

@@ -15,7 +15,13 @@ while True:
 
     if option == 'MILESTONE 3: FINE-TUNED':
 
-        st.write('TESTING1')
+        model_name = "distilbert-base-uncased-finetuned-sst-2-english"
+        model = AutoModelForSequenceClassification.from_pretrained(model_name)
+        tokenizer = AutoTokenizer.from_pretrained(model_name)
+        classifier = pipeline(task="sentiment-analysis", model=model, tokenizer=tokenizer)
+        preds = classifier(textIn)
+        preds = [{"score": round(pred["score"], 4), "label": pred["label"]} for pred in preds]
+        st.write('According to Pipeline, input text is ', preds[0]['label'], ' with a confidence of ', preds[0]['score'])
 
         # model_name_0 = "Rathgeberj/milestone3_0"
         # model_0 = AutoModelForSequenceClassification.from_pretrained(model_name_0)
@@ -51,6 +57,9 @@ while True:
         # tokenizers = [tokenizer_0, tokenizer_1, tokenizer_2, tokenizer_3, tokenizer_4, tokenizer_5]
         # classifiers = [classifier_0, classifier_1, classifier_2, classifier_3, classifier_4, classifier_5]
 
+        # X_train = [textIn]
+        # batch = tokenizer(X_train, padding=True, truncation=True, max_length=512, return_tensors="pt")
+
         
         # st.write('TESTING2')