Clément Chadebec retweeted
Introducing Praxis-1, an open-weight World Action Model that turns our video pre-training expertise into real world control for robots.
Robot demonstration data is limited. But video data is infinite. Praxis-1 extends our bet that the best policy models will learn from video, and use that scale to bring embodied intelligence to every industry.
Praxis-1 is built on our large-scale video pre-training and real-time infrastructure, and acts as a policy model for robotics developers and researchers that works across any embodiment or environment, no matter how complex.
We are actively testing with early partners including Noble Machines, Standard Bots and Ultra, and will be releasing the weights publicly in the coming months.
Learn more and request early access at runway.com/Praxis-1
Clément Chadebec retweeted
Exciting news from Jasper Research! 🚀
We built an internal 4B text-to-image model from scratch that turned out to be one of the fastest models out there!
1k image generation in less than a second!
Our technical report shares everything we learned along the way.
👇
Clément Chadebec retweeted
very nice dataset drop from the clipdrop team 🙌
📢 New @heyjasper release ! 📢
MONET 🌸 : An Apache2.0 deduped and recaptioned dataset of 105M samples unlocking reproducible text-to-image research.
Nano T2I 🖌️ : A codebase to train your own T2I model
🤗 @huggingface: huggingface.co/datasets/jasp…
💻: github.com/gojasper/nano-t2i
Very excited about this new release, pushing the boundaries of open and reproducible T2I research.
Congrats to the team!
Benjamin Aubin Gonzalo Quintana @onurxtasar @UlaLaParis @_jeev2 @dh7net @clipdropapp @heyjasperai
Clément Chadebec retweeted
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 🔥
Clément Chadebec retweeted
wow 🤯
68 TB, high-quality, high-resolution, Apache 2.
Thank you! 🙌🫡
📢 New @heyjasper release ! 📢
MONET 🌸 : An Apache2.0 deduped and recaptioned dataset of 105M samples unlocking reproducible text-to-image research.
Nano T2I 🖌️ : A codebase to train your own T2I model
🤗 @huggingface: huggingface.co/datasets/jasp…
💻: github.com/gojasper/nano-t2i
Very excited about this new release, pushing the boundaries of open and reproducible T2I research.
Congrats to the team!
Benjamin Aubin Gonzalo Quintana @onurxtasar @UlaLaParis @_jeev2 @dh7net @clipdropapp @heyjasperai
Clément Chadebec retweeted
Ah! this is insane, I've been complaining for weeks about the lack of open text-to-image data! Congrats on the release @heyjasperai
📢 New @heyjasper release ! 📢
MONET 🌸 : An Apache2.0 deduped and recaptioned dataset of 105M samples unlocking reproducible text-to-image research.
Nano T2I 🖌️ : A codebase to train your own T2I model
🤗 @huggingface: huggingface.co/datasets/jasp…
💻: github.com/gojasper/nano-t2i
Very excited about this new release, pushing the boundaries of open and reproducible T2I research.
Congrats to the team!
Benjamin Aubin Gonzalo Quintana @onurxtasar @UlaLaParis @_jeev2 @dh7net @clipdropapp @heyjasperai
Clément Chadebec retweeted
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 👏
📢 New @heyjasper release ! 📢
MONET 🌸 : An Apache2.0 deduped and recaptioned dataset of 105M samples unlocking reproducible text-to-image research.
Nano T2I 🖌️ : A codebase to train your own T2I model
🤗 @huggingface: huggingface.co/datasets/jasp…
💻: github.com/gojasper/nano-t2i
Very excited about this new release, pushing the boundaries of open and reproducible T2I research.
Congrats to the team!
Benjamin Aubin Gonzalo Quintana @onurxtasar @UlaLaParis @_jeev2 @dh7net @clipdropapp @heyjasperai
Clément Chadebec retweeted
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
📢 New @heyjasper release ! 📢
MONET 🌸 : An Apache2.0 deduped and recaptioned dataset of 105M samples unlocking reproducible text-to-image research.
Nano T2I 🖌️ : A codebase to train your own T2I model
🤗 @huggingface: huggingface.co/datasets/jasp…
💻: github.com/gojasper/nano-t2i
Very excited about this new release, pushing the boundaries of open and reproducible T2I research.
Congrats to the team!
Benjamin Aubin Gonzalo Quintana @onurxtasar @UlaLaParis @_jeev2 @dh7net @clipdropapp @heyjasperai
Clément Chadebec retweeted
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
Clément Chadebec retweeted
Object Relighting with Latent Bridge Matching
Link to Hugging Face space below + Link to Kijai's ComfyUI wrapper in first comment 👇
Clément Chadebec retweeted
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.
📢 Latent Bridge Matching update! 📢
New @heyjasperai release 🚀
- 3 LBM models on @huggingface (relighting, depth, normals)
- LBM training code
Also see our @Gradio space for object relighting!
🤗 huggingface.co/jasperai/LBM_…
💻 github.com/gojasper/LBM
📗 arxiv.org/abs/2503.07535
Clément Chadebec retweeted
Very proud of the team!
📢 Latent Bridge Matching update! 📢
New @heyjasperai release 🚀
- 3 LBM models on @huggingface (relighting, depth, normals)
- LBM training code
Also see our @Gradio space for object relighting!
🤗 huggingface.co/jasperai/LBM_…
💻 github.com/gojasper/LBM
📗 arxiv.org/abs/2503.07535
Clément Chadebec retweeted
🔥Wanna talk about combining diffusion models and sampling ?🔥
I'll be attending ICLR next week to present my work (main track + FPI workshop) with the one and only @theh2o64, we'll be pleased to discuss about this hot topic. See you there !
Clément Chadebec retweeted
Introducing Mistral Small 3.1.
Multimodal, Apache 2.0, outperforms Gemma 3 and GPT 4o-mini.
mistral.ai/news/mistral-smal…
Clément Chadebec retweeted
New research drop! Our team at Jasper is redefining image-to-image translation with LBM: Latent Bridge Matching—a scalable approach to high-speed AI-powered image transformation. See it in action!
Excited to share our new research at @heyjasperai !🚀
LBM: Latent Bridge Matching for Fast Image-to-Image Translation
Try out our @huggingface space for object relighting!
🤗@Gradio demo: huggingface.co/spaces/jasper…
👉Paper: arxiv.org/abs/2503.07535
💻Repo: github.com/gojasper/LBM
Clément Chadebec retweeted
Yesss @heyjasperai introduces LBM: Latent Bridge Matching for Fast Image-to-Image Translation💡
and drops an amazing ✨image relighting✨ demo that runs with a single(!) inference step 🔥
Clément Chadebec retweeted
I can't be more proud of the team!
Excited to share our new research at @heyjasperai !🚀
LBM: Latent Bridge Matching for Fast Image-to-Image Translation
Try out our @huggingface space for object relighting!
🤗@Gradio demo: huggingface.co/spaces/jasper…
👉Paper: arxiv.org/abs/2503.07535
💻Repo: github.com/gojasper/LBM
