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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
```
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Size of downloaded dataset files:
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Size of the auto-converted Parquet files:
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Number of rows:
9,980