update app.py

app.py

@@ -15,15 +15,14 @@ from transformers import (
 
 # model_path = "EmotiScan/amazon-comments-bert" # To use your model, on line 55, you'll have to change i to i+1
 # model_path = "nlptown/bert-base-multilingual-uncased-sentiment"
-model_path = "EmotiScan/amazon-comments-bert"
+model_path = "Mofe/emotiscan_model_2"
 
 tokenizer = AutoTokenizer.from_pretrained(model_path)
 model = AutoModelForSequenceClassification.from_pretrained(model_path)
 
 
-description = f"""# <h2 style="text-align: center;"> EmotiScan Amazon Products Review</h2>
-<p style="text-align: center;font-size:15px;"> (Placeholder description) Analysing Amazon product reviews...
-Input a single review to predict sentiment or multiple from a text file.</p>
+description = f"""# <h2 style="text-align: center;"> Opinion Orbit Amazon Products Review</h2>
+<p style="text-align: center;font-size:15px;"> Input a single review to predict sentiment or multiple from a text file.</p>
 """
 
 sample_reviews = [
@@ -52,7 +51,7 @@ def get_sentiments(text):
         logits = model(**encoded_input).logits
 
     logits_list = logits[0].tolist()
-    logits_labels = [model.config.id2label[i + 1]
+    logits_labels = [model.config.id2label[i]
                      for i in range(0, len(logits_list))]
 
     probs = softmax(logits_list)