Upload app.py

app.py

@@ -0,0 +1,36 @@
+import streamlit as st
+import torch
+
+model = torch.load("./model.pt")
+st.title("Analisis de Sentimientos")
+txt = st.text_area(label="Please write what you want to analyze...")
+
+def run_sentiment_analysis (txt) :
+    THRESHOLD = 0.5
+    
+    encoding = tokenizer.encode_plus(
+        txt,
+        add_special_tokens=True,
+        max_length=512,
+        return_token_type_ids=False,
+        padding="max_length",
+        return_attention_mask=True,
+        return_tensors='pt',
+    )
+
+    _, test_prediction = model(encoding["input_ids"], encoding["attention_mask"])
+    test_prediction = test_prediction.flatten().numpy()
+
+    predictions = []
+    print('-------------------- Predictions ---------------------')
+
+    for label, prediction in zip(LABEL_COLUMNS, test_prediction):
+        if prediction < THRESHOLD:
+            continue
+        predictions.append(" ".join([label,str(prediction)]))
+        return predictions
+
+predictions = run_sentiment_analysis(txt)
+for prediction in predictions:
+    st.write(prediction)
+