Viewing profile — schopra909

I’m not entirely sure if local development will lead to Nvidia’s supremacy being challenged. I think a simple reason why it’s been hard to unseat in Nvidia is first mover advantage…

100% agreed.

Honestly never considered the forking use case; but it makes a ton of sense when explained Congrats on the launch. This is cool tech

Really cool to see innovation in terms of quality of tiny models. Great work!

Very cool work! We spend a lot of time thinking about "robust representations" in the video space. Are there any alternative ideas to JEPA right now, when it comes to speech encodi…

Honest question, why were folks posting AI generated comments in the first place? There's such a high inertia to comment. I only comment when I have something to contribute OR find…

It’s a great question. In terms of pre-training even if they were was enough data at that quality, storing it and either demuxing it into raw frames OR compressing it with a suffic…

honestly, it's really hard to shorten the feedback loop in this space. For this, we really just did run one experiment at a time and visually inspect the results everywhere. when y…

Hadn’t seen that before! Seems very in line with what with the broader points about regularization. In table 4 they show faster convergence in 200 epochs when used alongside REPA. …

yep, Apache 2.0! so anyone's welcome to download and hack away

Hi HN, I’m one of the two authors of the post and the Linum v2 text-to-video model ( https://news.ycombinator.com/item?id=46721488 ). We're releasing our Image-Video VAE (open weig…

This is very cool. Side note, I really dig the JavaScript animations on the causal block diffusion blog post. Made the concept immediately clear

That all being said, you can just delete the T5 from memory after encoding the text so save on memory. The 2B parameters will take up 4 Gb of memory but activations will be a lot m…

Great idea! We haven’t tried it but def interested to see if that works as well. When we started down this path, T5 was the standard (back in 2024). Likely won’t be the text encode…

I think YC just release video on the basics of diffusion, but honestly I don’t have a good end to end guide. We’re going to write up going 0->1 on a video model (all the steps) ove…

https://www.linum.ai/field-notes

Not public yet — we’re going to clean it up so it’s readable and release it as blog posts. First one will be everything you need to know on building a VAE for image and video. Shou…

T5 Encoder is ~5B parameters so back of the envelope would be ~10GB of VRAM (it's in bfloat16). So, for 360p should take ~15 GB RAM (+/- a few GB based on the duration of video gen…

Per the RAM comment, you may able to get it run locally with two tweaks: https://github.com/Linum-AI/linum-v2/blob/298b1bb9186b5b9ff6... 1) Free up the t5 as soon as the text is en…

Should be fixed now! Thanks again for the heads up

Oh damn! Thanks for catching that -- going to ping the HF folks to see what they can do to fix the collection link. In the meantime here's the individual links to the models: https…

Writeup (includes good/bad sample generations): https://www.linum.ai/field-notes/launch-linum-v2 We're Sahil and Manu, two brothers who spent the last 2 years training text-to-vide…