Initial app.py changes

Created an App to tokenize, create embeddings using a specialized Medical model.

app.py

@@ -0,0 +1,26 @@
+import streamlit as st
+from transformers import AutoModel, AutoTokenizer
+import torch
+
+# The model name
+model_name = "emilyalsentzer/Bio_ClinicalBERT"
+
+# Load the tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModel.from_pretrained(model_name)
+
+# Streamlit app UI
+st.title("Medical Text Analysis with ClinicalBERT")
+st.write("Type in a medical text input to get the CLS token embedding.")
+
+# User input
+text = st.text_input("Enter Medical Text")
+
+if st.button("Predict"):
+    if text.strip():
+        inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True, max_length=512)
+        outputs = model(**inputs)
+        cls_embedding = outputs.last_hidden_state[:, 0, :].detach().numpy()
+        st.write(f"CLS Embedding (first 5 values): {cls_embedding[0][:5]}")
+    else:
+        st.write("Please enter some text.")