Multiple models added

app.py

@@ -6,19 +6,23 @@ st.header("This app is to analyze the sentiments behind a text. Currently it use
           pre-trained models without fine-tuning.")
 
 user_input = st.text_input("Enter your text:", value="Missing Sophie.Z...")
-st.selectbox("Please select a model:", ("Model 1", "Model 2", "Model 3"))
-
-
-
-if st.button("Analyze"):
-    model_name = "distilbert-base-uncased-finetuned-sst-2-english"
+user_model = st.selectbox("Please select a model:", 
+                          ("distilbert-base-uncased-finetuned-sst-2-english",
+                           "cardiffnlp/twitter-roberta-base-sentiment", 
+                           "finiteautomata/bertweet-base-sentiment-analysis"))
 
+def analyze(model_name, text):
     model = AutoModelForSequenceClassification.from_pretrained(model_name)
     tokenizer = AutoTokenizer.from_pretrained(model_name)
-
     classifier = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
-    res = classifier(user_input)
-    st.write(res)
-    
+    return classifier(text)
+
+
+if st.button("Analyze"):
+    if not user_input:
+        st.write("Please enter a text.")
+    else:
+        with st.spinner("Hang on.... Analyzing..."):
+            st.write(analyze(user_model, user_input))
 else:
     st.write("Go on! Try the app!")

milestone3.py

@@ -14,10 +14,22 @@ res = classifier(["I am very happy now.", "Not happy now."])
 for result in res:
     print(result)
 
+# Separate each word as a token
 tokens = tokenizer.tokenize("I am very happy now.")
+
+# Generate a list of IDs, each ID for each token
 token_ids = tokenizer.convert_tokens_to_ids(tokens)
+
+# Return a dict with IDs
 input_ids = tokenizer("I am very happy now.")
 
 print(f'Tokens:{tokens}')
 print(f'TokenIDs:{token_ids}')
 print(f'InputIDs:{input_ids}')
+
+X_train = ["We are very happy to show you the Transformers library.", 
+           "Hope you don't hate it"]
+
+batch = tokenizer(X_train, padding=True, truncation=True, max_length=512, return_tensors="pt")
+
+

requirements.txt

@@ -1,2 +1,2 @@
 transformers
-pytorch
+torch