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README.md
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---
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size_categories:
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- 10K<n<100K
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pretty_name: OKReddit Visionary
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task_categories:
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- text-generation
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- fill-mask
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task_ids:
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- language-modeling
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- masked-language-modeling
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source_datasets:
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- original
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language:
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- en
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---
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<div>
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<a href="https://cdn-uploads.huggingface.co/production/uploads/633e85093a17ab61de8d9073/jh7lskqN9TnF53HmKnFlh.png"><img src="https://cdn-uploads.huggingface.co/production/uploads/633e85093a17ab61de8d9073/jh7lskqN9TnF53HmKnFlh.png" title=""We've switched style models from 1.5 to SDXL! Yay! And yes, it's a Style lora once more."" style="margin-left:auto;margin-right:auto"></a>
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</div>
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# Dataset Summary
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OKReddit Visionary is a collection of **50 GiB** (~74K pairs) of image Question & Answers. This dataset has been prepared for research or archival purposes.
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This dataset includes (obviously) a filtered list of subreddits.
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- **Curated by:** KaraKaraWitch
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- **Funded by:** Recursal.ai
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- **Shared by:** KaraKaraWitch
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- **Language(s) (NLP):** Mainly English. Other languages are available at smaller sizes.
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- **License:** `Scripts` folder are Apache 2.0. Refer to [Licensing Information](#licensing-information) for data license.
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### Dataset Sources
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- **Source Data:** [Academic Torrents](https://academictorrents.com/details/9c263fc85366c1ef8f5bb9da0203f4c8c8db75f4) by (stuck_in_the_matrix, Watchful1, RaiderBDev & pushshift folks.)
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## Languages
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All the questions and answers should be in english at this size point.
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## Dataset Structure
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### Data Instances
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The dataset can be loaded with webdataset. Do note that there are multiple extensions to check: `jpg`, `jpeg` or `png`. They have not been reconverted to preserve the original file from reddit.
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```py
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import webdataset as wds
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# After concatting, you may use the file like a regular dataset.
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# The dataset is compatible with WebDataset format. Example...
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tar_file = "PackedTar.tar"
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hf_dataset = wds.WebDataset(str(tar_root)).decode("pil")
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```
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