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
Update README.md
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README.md
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pipeline_tag: text-to-image
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# Training continues.
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Trainer updated aka trainer.py with the updated version that handles checkpoint saving and loading using the correct comfyui script.
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pipeline_tag: text-to-image
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# CKPT Bumbles
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Apologies, the safetensors ARE comfyui formatted... CKPT. :V
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Rename the extension to ckpt, because it's clearly incorrect. I'll convert them asap, my apologies for not micro-managing more closely.
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I renamed epoch 4 in the repo.
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# Training continues.
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Trainer updated aka trainer.py with the updated version that handles checkpoint saving and loading using the correct comfyui script.
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