🆕 New AT-J LoRA
Took HiDream for a test drive and a new AT-J LoRa was the result.
Very smooth learning process overall. Images include prompts and the ComfyUI workflow, as they should.
Is HiDream good?
HiDream is showing real promise as a future base model. Training runs are super smooth, if a bit slow or expensive. Probably both. But that’s likely just a temporary bottleneck until the optimizer nerds finish their work and I can train LoRAs on my toaster.
It’s probably too good of a model. It’ll happily pick up and reflect whatever shit exist in your dataset. Garbage in, garbage out, just really, really nicely rendered garbage.
Training details
Trained with
diffusion-pipeon a RunPod A40. Cost: 5$Used the following configs:
config.toml
https://pastebin.com/YUGnKEPC
dataset.toml (key settings):
resolutions = [1024]
enable_ar_bucket = true
min_ar = 0.5
max_ar = 2.0
num_ar_buckets = 9
[[directory]]
path = '/workspace/dataset/atj'
Tried local training on a 4090, but even with block swapping enabled, diffusion-pipe decided to crash and burn. If you get it running locally, let me know how by joining the worst Discord community ever. We have a climate change denier who is quite the funny guy:
👉 https://discord.gg/PSa9EMEMCe
Lewd stuff currently in process...
Description
FAQ
Comments (21)
Thank you for sharing the training settings and cost! Was wondering about that, I know it's currently unoptimized so will see what they come up with.
Looks like the skin is better than flux
Clearly you've been spending way too much time looking at the Kardashians, if you think this is "better".
So we can not train hidream lora on a 3090 24gb?
I love the model, but i suspect this will kill it
I'm training one right now, using the nf4 for the transformer_dtype instead of float8. I have blocks_to_swap on 28. Using 23.5gb and taking 6.5 seconds per step.
@pointaveugle Interesting. 6.5 seconds per step sounds way to slow, but the fact its possible is a good sign
m4max with 64GB Ram/vrRam. no Problem training loras over here...
Consumer Nvidia graphics cards will probably not be of much use in the AI sector in the future.
it is still early, tools are just coming out. Onetrainer working on it, do not know about koyha. Still trying to use simpletuner on my 3090 also. I really am trying to avoid nf4 as the results are not really desirable.
i can confirm ai-toolkit works, however that was on a 48 gig vram 6000, hopefully Ostris can reduce memory needed soon
@NorfolkDave Looks like DIffusionPipe got LoRa training working on a 4090 with Block swapping https://github.com/tdrussell/diffusion-pipe
simpletuner works on WSL with 24gb gpu and 32gb ram with 24gb swap
Pretty good likeness. First hidream lora I found, so wanted to try it. Not sure about hidream yet; can't seem to get rid of some generation artifacts (a bit noisy) and while content is good, doesn't seem like as much randomness... will probably get better as more support arrives. Thanks!
Great LORA and amazing skin. I'm not sure why Redditors are saying they don't like it. A lot of Flux bros have gotten their wankers broken with HiDream. HiDream is the natural Flux replacement IMO. Does better images, uses LLM for better prompts, better coherence, and does fantastic text.
How does one use the lora? Just putting it in and loading it does nothing as if the lora isn't used at all or maybe its just comfyui that doesn't work?
I am also facing this issue, did you manage to resolve it?
@MalluLover6969 started using the official comfyui workflow and added the lora in between model and SD3sampling and it worked
How did you train this LORA? Did you use Simple Tuner? I have a 5090 and I just CANNOT get it to work. I even spent days trying. It just shoots up to more vram even with int8 quants set. I followed the guide exactly, too.
They were training on a runpod that uses an a40 (48 gb vram) and not local hardware. I do the same thing for my lora when I cant create them locally. I use ai-toolkit since it installs pretty quickly and boots up a UI. I just ssh into the runpod. Run the install script for ai-toolkit. Boot up the ui. Upload my dataset. Setup the training parameters. Run. Download checkpoints. Delete the instance. I typically only pay 3-5 dollars per Lora this way.
@rusty2930 I ended up getting it to work on my 5090 using TDRussel
Thanks for the update!
Alright folks,
Okay, nerds of the internet - who's got the lowdown / any pointers on training LORA for HiDream locally on a beastly RTX 4090, ideally sticking to the diffusion pipe? Anyone wrestled this particular beast before? Example toml config files? Yeah, hit me with those!
Cheers, folks!
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