oompty · HackerTrans

قبل 5 أشهرdiscuss

Ohh so that's how that happened. I had noticed (purely for research purposes of course) that some of Google's own keys hardcoded into older Android images were useable for Gemini (some instantly ratelimited so presumably used by many other people already but some still usable) until they all got disabled as leaked like two months ago. They also had over time disabled Gemini API access on some of them over them beforehand.

oompty

قبل 8 أشهرdiscuss

I'm surprised that Discord isn't part of that ban since it seems so much more social media like. One could argue that it has much smaller private and semi-private groups but there are large servers with hundreds of thousands or even millions of users that are basically the same as Reddit content and user wise.

oompty

قبل 8 أشهرdiscuss

Almost all streamers have some thirdparty "tip/donation" system set up (usually streamelements/streamlabs via paypal or stripe, sometimes also giving some TTS effects on stream) so that's still possible.

oompty

قبل 9 أشهرdiscuss

Really? After teaching/mentoring new devs and interns for the last two years at my job I definitely think there's plenty of space and opportunity for improvements on version control systems over git, large files and repos being one thing but primarily on user friendliness and accessibility where even existing ones like mercurial do a much nicer job in many ways.

oompty

قبل 12 شهرًاdiscuss

The model looks incredible!

Regarding this part: > Since flux-dev-raw is a guidance distilled model, we devise a custom loss to finetune the model directly on a classifier-free guided distribution.

Could you go more into detail on the specific loss used for this and any other possible tips for finetuning this that you might have? I remember the general open source ai art community had a hard time with finetuning the original distilled flux-dev so I'm very curious about that.

oompty

قبل 12 شهرًاdiscuss

The model looks incredible!

Regarding this part: > Since flux-dev-raw is a guidance distilled model, we devise a custom loss to finetune the model directly on a classifier-free guided distribution.

Could you go more into detail on the loss used for this and other possible tips for finetuning those? I remember the general open source ai art community had a hard time with finetuning the original distilled flux-dev so I'm very curious about that.

oompty

السنة الماضيةdiscuss

What about ones trained on fully licensed art, like Adobe Firefly (based on their own stock library) or F-Lite by Freepik & Fal (also claimed to be copyright safe)?

comments