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README.md
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- name: imUrl
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dtype: string
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- name: salesRank
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- name: Arts, Crafts & Sewing
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dtype: int64
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- name: Automotive
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dtype: int64
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- name: Baby
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dtype: int64
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- name: Beauty
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dtype: int64
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- name: Books
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dtype: int64
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- name: Camera & Photo
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dtype: int64
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- name: Cell Phones & Accessories
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dtype: int64
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- name: Clothing
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dtype: int64
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- name: Computers & Accessories
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dtype: int64
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- name: Electronics
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dtype: int64
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- name: Grocery & Gourmet Food
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dtype: int64
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- name: Health & Personal Care
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dtype: int64
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- name: Home & Kitchen
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dtype: int64
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- name: Home Improvement
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dtype: int64
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- name: Industrial & Scientific
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dtype: int64
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- name: Jewelry
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dtype: int64
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- name: Kitchen & Dining
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dtype: int64
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- name: Magazines
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dtype: int64
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- name: Movies & TV
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dtype: int64
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- name: Music
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dtype: int64
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- name: Musical Instruments
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dtype: int64
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- name: Office Products
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dtype: int64
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- name: Patio, Lawn & Garden
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dtype: int64
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- name: Pet Supplies
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dtype: int64
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- name: Shoes
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dtype: int64
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- name: Software
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dtype: int64
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- name: Sports & Outdoors
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dtype: int64
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- name: Toys & Games
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dtype: int64
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- name: Watches
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dtype: int64
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- name: categories
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sequence: string
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- name: price
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dtype: float64
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- name: related
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- name: also_bought
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sequence: string
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- name: also_viewed
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sequence: string
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- name: bought_together
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sequence: string
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- name: buy_after_viewing
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sequence: string
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- name: brand
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dtype: string
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- name: docno
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dtype: string
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- name: text
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dtype: string
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- name: __index_level_0__
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dtype: int64
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splits:
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- name: train
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num_bytes:
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num_examples: 259204
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download_size:
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dataset_size:
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---
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# Dataset Card for "amazon-text4rec"
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- name: imUrl
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dtype: string
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- name: salesRank
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dtype: string
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- name: categories
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dtype: string
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- name: price
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dtype: float64
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- name: related
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dtype: string
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- name: brand
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dtype: string
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- name: docno
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dtype: string
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- name: text
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dtype: string
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splits:
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- name: train
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num_bytes: 339201466
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num_examples: 259204
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download_size: 151776866
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dataset_size: 339201466
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---
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# Dataset Card for "amazon-text4rec"
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