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@@ -63,6 +63,17 @@ configs:
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  # Amazon All Beauty Dataset
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  ## Usage
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  ### Download metadata
@@ -73,4 +84,14 @@ metadata = load_dataset(path="smartcat/Amazon_All_Beauty_2018", name="metadata",
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  ### Download reviews
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  ```python
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  metadata = load_dataset(path="smartcat/Amazon_All_Beauty_2018", name="reviews", split="train")
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- ```
 
 
 
 
 
 
 
 
 
 
 
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  # Amazon All Beauty Dataset
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+ ## Directory Structure
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+
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+ - **metadata**: Contains product information.
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+
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+ - **reviews**: Contains user reviews about the products.
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+
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+ - **filtered**:
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+ - **e5-base-v2_embeddings.jsonl**: Contains "asin" and "embeddings" created with [e5-base-v2](https://huggingface.co/intfloat/e5-base-v2).
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+ - **metadata.jsonl**: Contains "asin" and "text", where text is created from the title, description, brand, main category, and category.
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+ - **reviews.jsonl**: Contains "reviewerID", "reviewTime", and "asin". Reviews are filtered to include only perfect 5-star ratings with a minimum of 5 ratings.
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+
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  ## Usage
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  ### Download metadata
 
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  ### Download reviews
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  ```python
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  metadata = load_dataset(path="smartcat/Amazon_All_Beauty_2018", name="reviews", split="train")
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+ ```
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+
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+ ### Download filtered files
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+ ```
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+ embeddibgs = load_dataset(
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+ path="smart cat/Amazon_All_Beauty_2018",
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+ data_files="filtered/reviews.jsonl",
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+ split="train",
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+ )
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+ ```
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+ **📎 Note:** You can set any file or list of files from the "filtered" directory as the "data_files" argument.