Spaces:
Runtime error
Runtime error
Upload app.py
Browse files
app.py
CHANGED
@@ -1,7 +1,11 @@
|
|
1 |
import streamlit as st
|
2 |
from transformers import pipeline
|
|
|
3 |
|
4 |
-
# Load the
|
|
|
|
|
|
|
5 |
classifier = pipeline("sentiment-analysis", model="Suphawan/website_classification")
|
6 |
|
7 |
def main():
|
@@ -17,9 +21,13 @@ def main():
|
|
17 |
classification_results = classifier([text])
|
18 |
category = classification_results[0]['label']
|
19 |
confidence = classification_results[0]['score']
|
|
|
|
|
|
|
20 |
|
21 |
st.write("Category:", category)
|
22 |
st.write("Confidence:", confidence)
|
|
|
23 |
|
24 |
if __name__ == "__main__":
|
25 |
main()
|
|
|
1 |
import streamlit as st
|
2 |
from transformers import pipeline
|
3 |
+
from sentence_transformers import SentenceTransformer
|
4 |
|
5 |
+
# Load the Sentence Transformers model
|
6 |
+
model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
|
7 |
+
|
8 |
+
# Load the website classification model (replace 'Suphawan/website_classification' with your actual model)
|
9 |
classifier = pipeline("sentiment-analysis", model="Suphawan/website_classification")
|
10 |
|
11 |
def main():
|
|
|
21 |
classification_results = classifier([text])
|
22 |
category = classification_results[0]['label']
|
23 |
confidence = classification_results[0]['score']
|
24 |
+
|
25 |
+
# Compute sentence embeddings
|
26 |
+
sentence_embeddings = model.encode([text])
|
27 |
|
28 |
st.write("Category:", category)
|
29 |
st.write("Confidence:", confidence)
|
30 |
+
st.write("Sentence Embeddings:", sentence_embeddings)
|
31 |
|
32 |
if __name__ == "__main__":
|
33 |
main()
|