Update app.py

app.py

@@ -2,12 +2,10 @@ import streamlit as st
 from transformers import AutoModel, AutoTokenizer
 import torch
 
-# Load the model and tokenizer
 model_name = "sentence-transformers/all-MiniLM-L6-v2"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModel.from_pretrained(model_name)
 
-# Function to get embeddings
 def get_embedding(text):
     inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
     with torch.no_grad():
@@ -18,11 +16,9 @@ def get_embedding(text):
 st.title("Text Embedding with all-MiniLM-L6-v2")
 st.write("Enter text to get its embedding:")
 
-# Input text from the user
-input_text = st.text_area("Input Text", "")
+input_text = st.text_input("Input Text", "")
 
-# If input text is provided, show the embeddings
 if input_text:
     embedding = get_embedding(input_text)
     st.write("Embedding:")
-    st.write(embedding.numpy())
+    st.write(embedding)