Create app.py

app.py

@@ -0,0 +1,20 @@
+import streamlit as st
+import tensorflow as tf
+
+from transformers import AutoTokenizer, TFAutoModelForSequenceClassification
+  
+tokenizer = AutoTokenizer.from_pretrained("Yah216/Sentiment_Analysis_CAMelBERT_msa_sixteenth_HARD")
+
+model = TFAutoModelForSequenceClassification.from_pretrained("Yah216/Sentiment_Analysis_CAMelBERT_msa_sixteenth_HARD")
+
+labels= model.config.label2id
+
+text = st.text_area("Enter some text!") 
+if text: 
+   out = tf.math.softmax(model(tokenizer(raw_inputs, padding=True, truncation=True, return_tensors="np")).logits, , axis = -1)
+   res = out.numpy()
+   
+   labels['NEGATIVE'] = res[0,0]
+   labels['NEUTRAL'] = res[0,1]
+   labels['POSITIVE'] = res[0,2]
+   st.json(labels)