Large image-text models like ALIGN, BASIC, Turing Bletchly, FLORENCE & GLIDE have shown better and better performance compared to previous flagship models like CLIP and DALL-E. Most of them had been trained on billions of image-text pairs and unfortunately, no datasets of this size had been openly available until now. To address this problem we present LAION 5B, a large-scale dataset for research purposes consisting of 5,85B CLIP-filtered image-text pairs. 2,3B contain English language, 2,2B samples from 100+ other languages and 1B samples have texts that do not allow a certain language assignment (e.g. names ). Additionally, we provide several nearest neighbor indices, an improved web interface for exploration & subset creation as well as detection scores for watermark and NSFW. We also announce a full reproduction of a clip training trained on LAION-400M at open_clip. Explore the dataset at the search demo. See also the same post on laion website .

After processing and filtering common crawl, 5,85B of URL/text samples remained. We did additional steps after that in order to prepare the dataset. See this semantic search blogpost and the readme of clip-retrieval for additional details about this process. See also semantic search at billions scale for more technical details of the process that was done for laion5B.


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The model, as well as the training code, are available at CLIP-based-NSFW-Detector The tags are available at laion2B-en-safety laion2B-multi-safety laion1B-nolang-safety Demo at clip-retrieval (check/uncheck safe mode)

I uploaded the database file itself using scp, and ran fly ssh console -a laion-aesthetic to SSH in and execute other commands such as datasette inspect laion-aesthetic-6pls.db > inspect.json to create the inspect JSON file. 2351a5e196

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