Text-to-Image
Diffusers
TensorBoard
stable-diffusion
diffusion
distillation
flow-matching
geometric-deep-learning
research
Instructions to use AbstractPhil/sd15-flow-matching with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AbstractPhil/sd15-flow-matching with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AbstractPhil/sd15-flow-matching", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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README.md
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This is the config for the PT, you want the student unless you want to train it
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I KNOW I KNOW, I'll get it worked out. For now this is every epoch 9+ if you see a PT for this particular model.
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```
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# Plan Update: 11/1/2025
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I'm sticking to the positive spectrum here, knowing that 6 million samples isn't enough to converge sd15.
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I believe it will take around 10 mil to start SEEING correct shapes showing with texture other than flat or blob, but I've been wrong before - and we will make happy little bushes out of this if I am.
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Our flow match troopers are trying their best, but the outlooks aren't looking particularly good yet. Blobs all the way to epoch 30.
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That's roughly 200,000 samples * 30, which should be about 6 million images worth. Not enough to fully saturate the system, but more than what I used for sdxl vpred conversions.
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There may need to be a refined process with synthetic dreambooth-styled images devoted to top prio, mid prio, and low prio classes.
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When the distillation concludes, there will be additional finetuning after with direct images generated from sd15 using class-based specifics in any case.
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So, it'll be an interesting outcome for both the baseline starter and the v2 trained version.
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I have high hopes either way and I will have the class-based dreambooth-style selector ready to immediately begin after epoch 50.
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# Earlier updates
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This is the config for the PT, you want the student unless you want to train it
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I KNOW I KNOW, I'll get it worked out. For now this is every epoch 9+ if you see a PT for this particular model.
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