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Update README.md

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@@ -53,6 +53,20 @@ CapyWiki contains 3 splits:
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  The dataset should contain photos, illustrations, scans, maps and any other media categories in an image format that Wikimedia hosts.
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  ## What's the intended use of CapyWiki
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  Using CapyWiki to train and evaluate neural networks is possible but not exclusive.
@@ -74,17 +88,3 @@ The dataset contains:
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  ## Help needed
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  This is a raw dataset. Tasks such as: captioning, content classification (photos, illustrations, etc.), aesthetic classifications, meta-data inclusion (width, height) or the images are open and community contributions for those are more than welcome.
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- ## Loading the dataset for downstream use-cases
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- The dataset splis are in a `*.parquet` format and can be read/processed by any tool or library that can read `*.parquet` files.
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-
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- If you wish to use the Hugging Face Datasets library you can load the dataset as:
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-
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- ```py
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- from datasets import load_dataset
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- #Load the public_domain split
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- dataset = load_dataset("opencapybara/CapyWiki-34M", split="public_domain")
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-
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- #Now the dataset can be used for any downstream cases e.g.:
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- # first_500_urls = dataset[:500]['url']
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- ```
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-
 
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  The dataset should contain photos, illustrations, scans, maps and any other media categories in an image format that Wikimedia hosts.
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+ ## Loading the dataset for downstream use-cases
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+ The dataset splis are in a `*.parquet` format and can be read/processed by any tool or library that can read `*.parquet` files.
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+
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+ If you wish to use the Hugging Face Datasets library you can load the dataset as:
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+
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+ ```py
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+ from datasets import load_dataset
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+ #Load the public_domain split
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+ dataset = load_dataset("opencapybara/CapyWiki-34M", split="public_domain")
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+
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+ #Now the dataset can be used for any downstream cases e.g.:
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+ # first_500_urls = dataset[:500]['url']
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+ ```
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+
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  ## What's the intended use of CapyWiki
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  Using CapyWiki to train and evaluate neural networks is possible but not exclusive.
 
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  ## Help needed
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  This is a raw dataset. Tasks such as: captioning, content classification (photos, illustrations, etc.), aesthetic classifications, meta-data inclusion (width, height) or the images are open and community contributions for those are more than welcome.
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