| # 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 | |
| ``` | |