commit14

app.py

@@ -318,7 +318,17 @@ metadata = fashion.remove_columns("image").to_pandas()
 bm25 = BM25Encoder()
 bm25.fit(metadata["productDisplayName"])
 model = SentenceTransformer('sentence-transformers/clip-ViT-B-32', device='cuda' if torch.cuda.is_available() else 'cpu')
+from sentence_transformers import SentenceTransformer
+import torch
+
+device = 'cuda' if torch.cuda.is_available() else 'cpu'
 
+# load a CLIP model from huggingface
+model = SentenceTransformer(
+    'sentence-transformers/clip-ViT-B-32',
+    device=device
+)
+model
 # ------------------- Hybrid Scaling -------------------
 def hybrid_scale(dense, sparse, alpha: float):