91–100 of 239 posts
Earlier quoted context omitted.
3090 TIs should be able to handle it without much in the way of tricks for a "reasonable" (for the HN crowd) price.
Why not on a CPU with 32 or 64 GB of RAM?
I wonder if the key behind the quality of the MidJourney models, and this models, is less about size + architecture and more about the quality of images trained on. It looks like this is the case for LLMs, that the training quality of the data has a significant impact on the output quality of the model, which makes sense. So the real magic is in designing a system to curate that high quality data.
Midjourney unquestionably has heavy data set curation and uses RLHF from users. You don't have to speculate on this as you can see that custom models for SDXL for instance perform vastly better than vanilla SDXL at the same number of parameters. It's all data set and tagging.
Earlier quoted context omitted.
Midjourney unquestionably has heavy data set curation and uses RLHF from users. You don't have to speculate on this as you can see that custom models for SDXL for instance perform vastly better than vanilla SDXL at the same number of parameters. It's all data set and tagging.
custom models perform vastly better at the tasks they are finetuned to do
hi friends! burkay from fal.ai here. would like to clarify that the model is NOT built by fal. all credit should go to Black Forest Labs ( https://blackforestlabs.ai/ ) which is a new co by the OG stable diffusion team. what we did at fal is take the model and run it on our inference engine optimized to run these kinds of models really really fast. feel free to give it a shot on the playgrounds. https://fal.ai/models…
You can try the models here: (available without sign-in) FLUX.1 [schnell] (Apache 2.0, open weights, step distilled): https://fal.ai/models/fal-ai/flux/schnell (requires sign-in) FLUX.1 [dev] (non-commercial, open weights, guidance distilled): https://fal.ai/models/fal-ai/flux/dev FLUX.1 [pro] (closed source [only available thru APIs], SOTA, raw): https://fal.ai/models/fal-ai/flux-pro
> (available without sign-in) FLUX.1 [schnell] (Apache 2.0, open weights, step distilled): https://fal.ai/models/fal-ai/flux/schnell Well, I was wondering about bias in the model, so I entered "a president" as the prompt. Looks like it has a bias alright, but it's even more specific than I expected...
[0] https://fal.media/files/elephant/gu3ZQ46_53BUV6lptexEh.png
Anyone know why text-to-image models have so many fewer parameters than text models? Are there any large image models (>70b, 400b, etc)?
The only reason that diffusion isn't used for text is because text requires discrete outputs.
hi friends! burkay from fal.ai here. would like to clarify that the model is NOT built by fal. all credit should go to Black Forest Labs ( https://blackforestlabs.ai/ ) which is a new co by the OG stable diffusion team. what we did at fal is take the model and run it on our inference engine optimized to run these kinds of models really really fast. feel free to give it a shot on the playgrounds. https://fal.ai/models…
The name is a bit unfortunate given that Julia's most popular ML library is called Flux. See: https://fluxml.ai . This library is quite well known, 3rd most starred project in Julia: https://juliapackages.com/packages?sort=stars . It has been around since, at least, 2016: https://github.com/FluxML/Flux.jl/graphs/code-frequency .
also search engines are context aware, if your search history is full of julia questions, it will know what you're searching for
Earlier quoted context omitted.
The name is a bit unfortunate given that Julia's most popular ML library is called Flux. See: https://fluxml.ai . This library is quite well known, 3rd most starred project in Julia: https://juliapackages.com/packages?sort=stars . It has been around since, at least, 2016: https://github.com/FluxML/Flux.jl/graphs/code-frequency .
There was a looong distracting thread a month ago about something similar, niche language, might have been Julia, had a package with the same name as $NEW_THING. I hope this one doesn't stir as much discussion. It has 4000 stars, there isnt a large mass of people who view the world through the lens of "Flux is ML library". No one will end up in a "who is on first?" discussion because of it. If this line of argument i…
You can try the models here: (available without sign-in) FLUX.1 [schnell] (Apache 2.0, open weights, step distilled): https://fal.ai/models/fal-ai/flux/schnell (requires sign-in) FLUX.1 [dev] (non-commercial, open weights, guidance distilled): https://fal.ai/models/fal-ai/flux/dev FLUX.1 [pro] (closed source [only available thru APIs], SOTA, raw): https://fal.ai/models/fal-ai/flux-pro
What is the difference between schnell and dev? Just the kind of distillation?
