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  - **Homepage:** [laion-5b](https://laion.ai/blog/laion-5b/)
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  - **Huggingface:** [laion/laion2B-multi](https://huggingface.co/datasets/laion/laion2B-multi)
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- - **Point of Contact: [mcg@mcemilg.dev](mailto:[email protected])**
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  ### Dataset Summary
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- [LAION-5B](https://laion.ai/blog/laion-5b/) is a large scale openly accessible image-text dataset contains text from multiple languages. This is a Turkish subset data of [laion/laion2B-multi](https://huggingface.co/datasets/laion/laion2B-multi).
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - **Homepage:** [laion-5b](https://laion.ai/blog/laion-5b/)
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  - **Huggingface:** [laion/laion2B-multi](https://huggingface.co/datasets/laion/laion2B-multi)
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+ - **Point of Contact:** [mcemilg](mailto:[email protected])
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  ### Dataset Summary
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+ [LAION-5B](https://laion.ai/blog/laion-5b/) is a large scale openly accessible image-text dataset contains text from multiple languages. This is a Turkish subset data of [laion/laion2B-multi](https://huggingface.co/datasets/laion/laion2B-multi). It's compatible to be used with [image2dataset](https://github.com/rom1504/img2dataset) to fetch the images at scale.
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+ ### Data Structure
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+ ```python
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+ DatasetDict({
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+ train: Dataset({
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+ features: ['SAMPLE_ID', 'URL', 'TEXT', 'HEIGHT', 'WIDTH', 'LICENSE', 'LANGUAGE', 'NSFW', 'similarity'],
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+ num_rows: 34638627
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+ })
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+ })
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+ ```
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+
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+ ```python
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+ {
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+ 'SAMPLE_ID': Value(dtype='int64', id=None),
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+ 'URL': Value(dtype='string', id=None),
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+ 'TEXT': Value(dtype='string', id=None),
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+ 'HEIGHT': Value(dtype='int64', id=None),
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+ 'WIDTH': Value(dtype='int64', id=None),
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+ 'LICENSE': Value(dtype='string', id=None),
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+ 'LANGUAGE': Value(dtype='string', id=None),
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+ 'NSFW': Value(dtype='string', id=None),
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+ 'similarity': Value(dtype='float64', id=None)
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+ }
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+ ```
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+
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+
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+ ### Notes
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+ The data was basically processed to drop non-Turkish and irrelevant texts before published. Both [FastText](https://fasttext.cc/docs/en/language-identification.html) and [langdetect](https://pypi.org/project/langdetect/) libraries were used to identify if the text is Turkish or not. The cleaning process can be summarized as follows:
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+
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+ - replace \"\"\" with empty str
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+ - remove URLs in texts
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+ - Drop if both FastText and LangDetect are highly confident with there is no Turkish in text.
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+ - Drop empty text fields.
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+
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+ ### License
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+ CC-BY-4.0
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+