Linum

We’re a 2-person lab researching more efficient architectures for generative image and video.

linum.ai/field-notes/pj…

Last month, we published Pyramid-JiT, a pixel-space architecture that converged 11x faster than its latent-diffusion counterpart.

Today, we're releasing a 2B Pyramid-JiT text-to-image model as a milestone towards more affordable video models.

Trained from scratch for only ~$20K.

See blog for details & weights (Apache 2.0).

New research, hot off the presses 🔥

We introduce a pixel-space image model (P-JiT) that matches our latent diffusion model in 11.3x fewer training samples.

linum.ai/field-notes/py…

See blog for details. Code and model checkpoints (Apache 2.0, as always).

Excited to release early research, on our road to Linum v3 text-to-video.

We introduce a novel pixel-space text-to-image architecture (JiT-DDT), that trains 3.6x faster than our old Linum v2 model.

linum.ai/field-notes/ji…

See the blog for the details, as well as code and model checkpoints (Apache 2.0).

Been heads down working on our next text-to-video model, but we're going to be publishing some exciting research updates over the next few weeks!

Here's an appetizer - How do you build pre-training datasets that accelerate model convergence?

linum.ai/field-notes/da…

Tools from the trenches. The first in a series of posts on how a two-person team ships foundation models (and maintains their sanity).