Enable Zero

app.py

@@ -15,7 +15,7 @@ from sentence_transformers import SentenceTransformer
 from dotenv import load_dotenv
 import os
 
-# import spaces
+import spaces
 import gradio as gr
 
 
@@ -81,20 +81,18 @@ def get_docs_from_parquet(parquet_urls, column, offset, limit):
     return df[column].tolist()
 
 
-# @spaces.GPU
+@spaces.GPU
 def calculate_embeddings(docs):
     return sentence_model.encode(docs, show_progress_bar=True, batch_size=32)
 
 
-# Adjust n_neighbors and n_components based on dataset size
 def calculate_n_neighbors_and_components(n_rows):
-    # Ensure n_neighbors is proportional to the dataset size, with reasonable limits
     n_neighbors = min(max(n_rows // 20, 15), 100)
     n_components = 10 if n_rows > 1000 else 5  # Higher components for larger datasets
     return n_neighbors, n_components
 
 
-# @spaces.GPU
+@spaces.GPU
 def fit_model(docs, embeddings, n_neighbors, n_components):
     global global_topic_model