xrailgun
xrailgun t1_j9avboh wrote
Reply to comment by wywywywy in [D] Large Language Models feasible to run on 32GB RAM / 8 GB VRAM / 24GB VRAM by head_robotics
Thanks!
I wish model publishers would indicate rough (V)RAM requirements...
xrailgun t1_j9aq903 wrote
Reply to comment by wywywywy in [D] Large Language Models feasible to run on 32GB RAM / 8 GB VRAM / 24GB VRAM by head_robotics
Did you test any larger and it wouldn't run?
Also, any comments so far among those? Good? Bad? Easy? Etc?
xrailgun t1_iur0bva wrote
Reply to [R] Is there any work being done on reduction of training weight vector size but not reducing computational overhead (eg pruning)? by Moose_a_Lini
Maybe 'Weight Agnostic Neural Networks' will help
xrailgun t1_ittjngu wrote
Reply to comment by Pitiful-You-8410 in [N] OpenAI Gym and a bunch of the most used open source RL environments have been consolidated into a single new nonprofit (The Farama Foundation) by jkterry1
<insert that xkcd here>
xrailgun t1_irc7qic wrote
Reply to comment by ECEngineeringBE in [R] Google announces Imagen Video, a model that generates videos from text by Erosis
In case you're serious, physics papers are crammed full of mathematical derivation first to logically support their hypotheses, then include all relevant conditions and parameters such that IF/WHEN you get access to the collider, key in the same, you could replicate them.
In ML, mathematical support still exists to varying degrees, but without sharing the source code, even if you had access to Google's/OpenAI's/Nvidia's billion dollar hardware, you can't replicate it.
xrailgun t1_ira22vy wrote
Reply to comment by ECEngineeringBE in [R] Google announces Imagen Video, a model that generates videos from text by Erosis
Shit straw man take.
xrailgun t1_j9dtp9c wrote
Reply to comment by Emergency_Apricot_77 in [D] Large Language Models feasible to run on 32GB RAM / 8 GB VRAM / 24GB VRAM by head_robotics
It might not be unreasonable to think maybe OP primarily wants the functionality of current LLMs, and if something can provide that more efficiently (or has promise to in the near future), s/he may want to know about it too.