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https://github.com/laion-ai/dataset-usage

This repository is a summary of all systems and scientific papers that use LAION datasets.
https://github.com/laion-ai/dataset-usage

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This repository is a summary of all systems and scientific papers that use LAION datasets.

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# dataset-usage
This repository is a summary of all systems and scientific papers that use LAION datasets.

## Papers citing LAION datasets

### LAION-5B

T.B.C.

### LAION-400M
After the release of LAION-400M, several papers used LAION-400M for image generation, text to image generation, image to text generation and text image matching:

- [Vector Quantized Diffusion Model for Text-to-Image Synthesis](https://arxiv.org/abs/2111.14822.pdf) used LAION-400M to train VQ diffusion text to image generation models
- [High-Resolution Image Synthesis with Latent Diffusion Models](https://arxiv.org/abs/2112.10752.pdf) used a subset of LAION-400M to train latent diffusion models
- [General Facial Representation Learning in a Visual-Linguistic Manner](https://arxiv.org/abs/2112.03109.pdf) LAION-400M face subset to train a face clip
- [BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation](https://arxiv.org/abs/2201.12086) image captioning using LAION-400M subset
- [MAGMA – Multimodal Augmentation of Generative Models through Adapter-based Finetuning](https://arxiv.org/pdf/2112.05253.pdf) was trained on image question answering using a LAION-400M subset

## Models trained on LAION datasets

### GLIDE finetuning

Clay Mullis (alias afiaka87) used subsets of LAON-2B to fine-tune the Open-AI Glide model and managed to reintroduce human generations.

- https://replicate.com/afiaka87/laionide-v3
- https://wandb.ai/afiaka87/glide_compare/reports/Finetuning-GLIDE-on-Laion5B–VmlldzoxNTg3MTkz
- https://wandb.ai/afiaka87/laionide-v3-glide/reports/Laionide-Version-3-Benchmark–VmlldzoxNjE0MTE3

### CLOOB

https://github.com/crowsonkb/cloob-training

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