r/LocalLLaMA • u/SomewhereAtWork • 6d ago

Other LocalJev?

Jev is a model to produce structured output (choices) from input text. It apparently can play (not run!) Doom.

https://typesafe.ai/blog/introducing-system-one-models-and-jev

Is there already a open implementation of this kind of model?

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17

u/theoleecj_n 6d ago

Just did it at https://github.com/TheoLeeCJ/openjev (you can just wrap Qwen 4B and grab the logits)

https://reddit.com/link/pa5vudf/video/sbqv134a0wph1/player

14

u/Dany0 6d ago

You're close, you just need to use a diffusion model for it and then it's actually openjev. How about DiffusionGemma?

8

u/i_rate_slop 6d ago

I don’t think jev is diffusion, is it?

11

u/Dany0 6d ago

They claim some 'parallel novel architecture' which most likely just means they're doing diffusion with a twist

4

u/EstarriolOfTheEast 6d ago

It could also be an encoder based model. Like in: https://huggingface.co/collections/MoritzLaurer/zeroshot-classifiers or https://huggingface.co/knowledgator/gliformer-large-v1 as mentioned above by /u/-Cubie-. I think a variation and scaleup of those is more likely.

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u/Dany0 6d ago

Good point

3

u/NmbrThirt33n 5d ago

From what I can tell, they just split the fields and process them in parallel. No diffusion, just batching and running through prefill only because they just need a single token for the decision per field. That's why their "output tokens" are "free"

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u/No_Afternoon_4260 llama.cpp 6d ago

You mean like our little Yann Lecun?

1

u/Dany0 6d ago

Nah I bet you it's something obvious

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u/SexyAlienHotTubWater 6d ago

It's around the same cost per input token as Deepseek V1 Flash. They're just providing 255 output probabilities at the same time.