@sean-mcleish.bsky.social
Reposted
New open source reasoning model!
Huginn-3.5B reasons implicitly in latent space 🧠
Unlike O1 and R1, latent reasoning doesn’t need special chain-of-thought training data, and doesn't produce extra CoT tokens at test time.
We trained on 800B tokens 👇
Huginn-3.5B reasons implicitly in latent space 🧠
Unlike O1 and R1, latent reasoning doesn’t need special chain-of-thought training data, and doesn't produce extra CoT tokens at test time.
We trained on 800B tokens 👇
February 10, 2025 at 3:58 PM
New open source reasoning model!
Huginn-3.5B reasons implicitly in latent space 🧠
Unlike O1 and R1, latent reasoning doesn’t need special chain-of-thought training data, and doesn't produce extra CoT tokens at test time.
We trained on 800B tokens 👇
Huginn-3.5B reasons implicitly in latent space 🧠
Unlike O1 and R1, latent reasoning doesn’t need special chain-of-thought training data, and doesn't produce extra CoT tokens at test time.
We trained on 800B tokens 👇
Reposted
Ok, so I can finally talk about this!
We spent the last year (actually a bit longer) training an LLM with recurrent depth at scale.
The model has an internal latent space in which it can adaptively spend more compute to think longer.
I think the tech report ...🐦⬛
We spent the last year (actually a bit longer) training an LLM with recurrent depth at scale.
The model has an internal latent space in which it can adaptively spend more compute to think longer.
I think the tech report ...🐦⬛
February 10, 2025 at 4:48 PM
Ok, so I can finally talk about this!
We spent the last year (actually a bit longer) training an LLM with recurrent depth at scale.
The model has an internal latent space in which it can adaptively spend more compute to think longer.
I think the tech report ...🐦⬛
We spent the last year (actually a bit longer) training an LLM with recurrent depth at scale.
The model has an internal latent space in which it can adaptively spend more compute to think longer.
I think the tech report ...🐦⬛