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README.md

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+
+    # Amazon Product Vector Database
+
+    This dataset contains vector embeddings for Amazon products, including both text and image embeddings.
+
+    ## Contents
+    - `embeddings.parquet`: Contains text embeddings, image embeddings, and metadata for all products
+
+    ## Usage
+    ```python
+    import pandas as pd
+    from datasets import load_dataset
+
+    # Load the dataset
+    dataset = load_dataset("chen196473/amazon_vector_database")
+    
+    # Read the data
+    df = pd.read_parquet("embeddings.parquet")
+    
+    # Extract embeddings
+    text_embeddings = df[[col for col in df.columns if col.startswith('text_embedding_')]].values
+    image_embeddings = df[[col for col in df.columns if col.startswith('image_embedding_')]].values
+    ```
+    

embeddings.parquet

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+oid sha256:bf91608cdd865b3da40f8a0d7a887a0d1c656a6a8ed438acaed3068d927063c0
+size 65902681