Text-to-Image
Diffusers
TensorBoard
Safetensors
stable-diffusion
diffusion
distillation
flow-matching
geometric-deep-learning
research
Instructions to use AbstractPhil/sd15-flow-lune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AbstractPhil/sd15-flow-lune 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-lune", 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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Currently retraining the scale, but it was trained with many raw unscaled latents and it makes the default output hazy.
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Use this to correctly orient the output to the correct VAE scale.
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Currently retraining the scale, but it was trained with many raw unscaled latents and it makes the default output hazy.
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Use this to correctly orient the output to the correct VAE scale.
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## Shift 2 is the training target
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Higher or lower may yield different results.
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## use this
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