Curious what's the actual cost for each edit? Will this infra always be reliable?
It's pretty impressive so far. Image quality isn't mind-blowing, but the multi-modal aspects are almost disturbingly powerful.
Not a lot of guardrails, either.
21–30 of 60 posts
Curious what's the actual cost for each edit? Will this infra always be reliable?
It's pretty impressive so far. Image quality isn't mind-blowing, but the multi-modal aspects are almost disturbingly powerful.
Not a lot of guardrails, either.
I left all the defaults as is, uploaded a small image, typed in "cafe," and 15 minutes later I am still waiting on this finishing.
I am working on a API to generate avatars/profile pics based on a prompt. I tried looking for train my own model bt I think it's a titanic task and impossible to do it myself. Is my best solution use an external API and then crop the face for what was generated?
The simplest commercial product for finetuning your own model is probably Adobe firefly, although there’s no API access support yet. But there are cheap and only slightly more involved options like Replicate or Civit.ai. Replicate has solid API support. Check out: https://replicate.com/blog/fine-tune-flux
Earlier quoted context omitted.
The simplest commercial product for finetuning your own model is probably Adobe firefly, although there’s no API access support yet. But there are cheap and only slightly more involved options like Replicate or Civit.ai. Replicate has solid API support. Check out: https://replicate.com/blog/fine-tune-flux
Is it Flux 1 possible to download and deploy to my own server? (And make a simple API on top of it?) I don't need fine tuning.
[flagged]
I left all the defaults as is, uploaded a small image, typed in "cafe," and 15 minutes later I am still waiting on this finishing.
Same, I left running for half an hour but nothing happened.
Elegant architecture, trained from scratch, excels at image editing. This looks very interesting! From https://arxiv.org/html/2409.11340v1 > Unlike popular diffusion models, OmniGen features a very concise structure, comprising only two main components: a VAE and a transformer model, without any additional encoders. > OmniGen supports arbitrarily interleaved text and image inputs as conditions to guide image generati…
> trained from scratch Not exactly. They mention starting from the VAE from Stable Diffusion XL and the Transformer from Phi3. Looks like these LLMs can really be used for anything