Update prepare.py

prepare.py

@@ -19,7 +19,7 @@ if __name__ == "__main__":
         df = ds.rename_columns({"img": "image", "label": "labels"}).to_pandas()
         df["label_str"] = df["labels"].apply(lambda x: ds.features["label"].int2str(x))
 
-        # df = df[:1000]
+        df = df.sample(10000, random_state=42).reset_index(drop=True)
 
         # precalculate umap embeddings
         df["embedding_ft_precalc"] = umap.UMAP(