updating index

app.py

@@ -9,11 +9,11 @@ with open("slugs_index_1024_cosine.pickle", "rb") as handle:
     index = pickle.load(handle)
 
 # Load model for computing embeddings.
-feature_extractor = AutoFeatureExtractor.from_pretrained("sasha/autotrain-butterfly-similarity-2490576840")
-model = AutoModel.from_pretrained("sasha/autotrain-butterfly-similarity-2490576840")
+feature_extractor = AutoFeatureExtractor.from_pretrained("sasha/autotrain-sea-slug-similarity-2498977005")
+model = AutoModel.from_pretrained("sasha/autotrain-sea-slug-similarity-2498977005")
 
 # Candidate images.
-dataset = load_dataset("sasha/butterflies_10k_names_multiple")
+dataset = load_dataset("sasha/australian_sea_slugs")
 ds = dataset["train"]
 
 
@@ -25,7 +25,7 @@ def query(image, top_k=4):
     inx = results[0][0].tolist()
     logits = results[1][0].tolist()
     images = ds.select(inx)["image"]
-    captions = ds.select(inx)["name"]
+    captions = ds.select(inx)["label"]
     images_with_captions = [(i, c) for i, c in zip(images,captions)]
     labels_with_probs = dict(zip(captions,logits))
     labels_with_probs = {k: 1- v for k, v in labels_with_probs.items()}

slugs_index_1024_cosine.pickle

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:001614717d03b205fa782c2e3f04b7556813d778be55e27426c6590b86a1a5c5
-size 20725122
+oid sha256:bdfd6d5f6f4b429f58395bd9225118f0f13bfc654ba2a8c1fdaef243792ddfcd
+size 20848578