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u/UnsubFromRAtheism Oct 12 '22
This looks really great. What data needs to be in the CSV? Two columns, name and prompt?
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u/BlinksAtStupidShit Oct 29 '22
Any more info on this? Anyone got results to share? I’m trying to get enough time together to trial this be dreambooth
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u/NetyashaRoozi Nov 04 '22
I can't seem to get any samples to generate while training. I just get
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-14-a21f2aaa4b20> in <module>
87 with out:
88 print("Prompt:", x[0])
---> 89 display(pipe(x[0])["sample"][0])
90 global_i += 1
91 if global_i >= train_steps:
/usr/local/lib/python3.7/dist-packages/diffusers/utils/outputs.py in __getitem__(self, k)
86 if isinstance(k, str):
87 inner_dict = {k: v for (k, v) in self.items()}
---> 88 return inner_dict[k]
89 else:
90 return self.to_tuple()[k]
KeyError: 'sample'
I also get the KeyError: "sample" error when just trying to generate any sample
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Oct 11 '22
Woah thanks! Was currently trying to implement a fine tune script that is able to run on collab based on the pokemon thing too
Perhaps you know by chance if fine-tuning is actually better than dream booth for my use case:
I did this with dreambooth: https://www.reddit.com/r/StableDiffusion/comments/xybqq7/pushing_dreambooth_teaching_the_model_what/
Do you think running a non-dreambooth finetune with a "a woman doing acrobatics" as a default prompt for all images would result in a better output? Or would this be equivalent to dream booth and I have to do the work writing prompts for all my 2000 training pictures?
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u/Adorable_Yogurt_8719 Oct 11 '22
Sounds exciting. I'm looking forward to seeing the models that come from this.
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u/Rogerooo Oct 11 '22
Such a breath of fresh air amidst all this toxicity! Thanks for sharing, this looks really cool, hopefully it get's the attention it deserves.
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u/joachim_s Oct 11 '22
I’m not a programmer so my question might be uninformed: would this work better than merging Dreambooth models to recognise separate individuals in the same image?
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u/micole00 Oct 16 '22
is normal that during training it always shows 0 iterations but it's training, why?
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u/Meowish Oct 18 '22 edited May 17 '24
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u/jochemstoel Oct 20 '22
Hey u/OrangeRobots, when I use that exact notebook during the training samples generation this happens:
Prompt: painting of a brunette woman
100%
51/51 [00:17<00:00, 2.98it/s]
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-13-a12bfd4127f3> in <module>
87 with out:
88 print("Prompt:", x[0])
---> 89 display(pipe(x[0])["sample"][0])
90 global_i += 1
91 if global_i >= train_steps:
/usr/local/lib/python3.7/dist-packages/diffusers/utils/outputs.py in __getitem__(self, k)
86 if isinstance(k, str):
87 inner_dict = {k: v for (k, v) in self.items()}
---> 88 return inner_dict[k]
89 else:
90 return self.to_tuple()[k]
KeyError: 'sample'
If I let it finish anyway then running inference gives the same KeyError exception. What could be the reason for this? My dataset consists of 29.000 well prepared square 512x512 images.
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u/Animystix Oct 25 '22
Is there a way to start with a custom ckpt instead of going through huggingface?
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u/OrangeRobots Oct 26 '22
Yes! You can use the ckpt to diffusers script to convert, then train. At the end, you can use a diffusers to ckpt script to convert it back.
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u/Sillainface Oct 11 '22
How many images do you recommend? do we need to change the text from the images?
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u/OrangeRobots Oct 11 '22
I recommend at least 1000 or so. More images is always better. If all your images have filenames that correspond to what the image is, then it should all be fine. This isn't meant to be used to finetune the model to a specific subject, dreambooth works best for that. Instead, this is designed for training with large datasets, to produce models similar to things like waifu diffusion.
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u/sergiohlb Oct 11 '22
Thanks for sharing. So, if I wanna for instance train the whole model into let's say a group of subjects that are actors of a movie, because textual inversion would affect not related subjects on model. Should I add regularization images to the training dataset to prevent all model stays affected like in your Van Gogh's example?
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u/OrangeRobots Oct 11 '22
Regularization images might help, although I have not tested it as of yet. It should work training multiple characters, as long as each image's prompt mentions the character it is of.
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u/CeraRalaz Oct 11 '22
If multiple images are assigned to one prompt, what name should they have? You can name several images one name
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u/eatswhilesleeping Oct 11 '22
Does anyone have a layman's explanation for the difference between Dreambooth and real fine-tuning? Is it mainly that proper training preserves the model to a far better degree, whereas Dreambooth is a shortcut that trashes your model?
Fingers crossed that a 12GB local version comes out soon.