Crawling@Home: Help Build The Worlds Largest Image-Text Pair Dataset!

1. DALLE-pytorch

   1 20 5,615 2.5 Python

   Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch

   

   Since then, several efforts have been organized to replicate DALL-E. People organized initially around this awesome dalle replication repository https://github.com/lucidrains/DALLE-pytorch with some nice results that can be seen in the readme. More recently as part of an huggingface events, new results have been achieved (see https://wandb.ai/dalle-mini/dalle-mini/reports/DALL-E-mini--Vmlldzo4NjIxODA ) and an online demo is now available https://huggingface.co/spaces/flax-community/dalle-mini

2. InfluxDB

   www.influxdata.com featured

   InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.

   

3. crawlingathome-worker

   2 2 10 0.0 Python

   

4. DALLE-datasets

   3 1 128 1.8 Python

   This is a summary of easily available datasets for generalized DALLE-pytorch training.

   

   A large part of the results that can be achieved with such models is thanks to data. Large amount of data. Today the largest open dataset for (image, text) pairs are in the order of 10M (see https://github.com/robvanvolt/DALLE-datasets ), which is enough to train okay models, but not enough to reach the best performance. Having a public dataset with hundred of millions of pairs could help a lot to build these image+text models.

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