faster

modular_graph_and_candidates.py

@@ -129,7 +129,9 @@ def embedding_similarity_clusters(models_root: Path, missing: List[str], thr: fl
     all_embeddings = []
 
     print(f"Encoding embeddings for {len(names)} models...")
-    batch_size = 1
+    batch_size = 8
+
+    names = names[:90]
     
     for i in tqdm(range(0, len(names), batch_size), desc="Models", leave=False):
         model_name = names[i]