After 8 months of long coding nights ☕️ we finally officially release Pythae 🥳, a python library unifying generative autoencoder implementations including vaegan🥗, vqvae or RAEs. 🖥️ github repo: github.com/clementchadebec/b… 👉paper: arxiv.org/abs/2206.08309

Feels quite magical to be able to clone a 68 TB dataset to my private HF training bucket while I only have a 4TB local disk, all of that in less than a minute thanks to HF infra optimizations & xet dedup!

very nice dataset drop from the clipdrop team 🙌

We are starting to be quite bullish about getting in the data infrastructure business. I just cloned 68 TB (while I only have a 4TB local disk) to my @huggingface training bucket in 1 minute 55 seconds, thanks to Xet deduplication and all our infra optimizations. You can host your data processing pipelines on HF and leverage those insane optimizations 🔥

wow 🤯 68 TB, high-quality, high-resolution, Apache 2. Thank you! 🙌🫡

Ah! this is insane, I've been complaining for weeks about the lack of open text-to-image data! Congrats on the release @heyjasperai

Huge open release from @heyjasperai : MONET 105M curated image-text pairs, Apache 2.0, with embeddings, VAE latents, multi-VLM captions, and a companion training repo (nano-t2i) to train a T2I model end-to-end on one H200 for <$300. Congrats @CChadebec & co 👏

With 104M of image-text pairs, this is one of the largest, if not the largest, openly-licensed image dataset And it's on @huggingface!! Kudos @heyjasperai

Flash Diffusion is a breakthrough in accelerating conditional diffusion models for image generation. Think fewer steps, faster results, and state-of-the-art quality. Here's what you need to know:

We’re thrilled to announce that the Jasper Research team’s latest paper on Latent Bridge Matching (LBM) was accepted to the prestigious IEEE/CVF International Conference on Computer Vision! Thank you @ICCVConference for the recognition, and congratulations to the team: @onurxtasar, Sanjeev Sreetharan, Benjamin Aubin, Gonzalo Quintana, @dh7net, and @CChadebec. LBM is a technique for rapid, high-fidelity image-to-image translation. Learn more about how LBM is changing visual marketing for retailers. bit.ly/3ZWMEcI

Object Relighting with Latent Bridge Matching Link to Hugging Face space below Link to Kijai's ComfyUI wrapper in first comment 👇

Proud to share the latest breakthrough from Jasper Research: Latent Bridge Matching (LBM) just got a major update! Our team has released three new open-source models on Hugging Face—supporting depth, normals, and relighting—along with training code and a Gradio demo for object relighting. This work continues our mission to advance controllable, high-quality AI image generation for enterprise marketing teams. 🔗 Explore the research, models, and demo: linkedin.com/feed/update/urn… 👏 Congrats to @CChadebec, Benjamin Aubin, @OnurXTasar, and @dh7net for pushing the field forward.

Very proud of the team!