Instructions to use valhalla/mad_max_diffusion-sd2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use valhalla/mad_max_diffusion-sd2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("valhalla/mad_max_diffusion-sd2", 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
- Draw Things
- DiffusionBee
Add `scale_factor` to vae config.
#2
by valhalla - opened
- vae/config.json +1 -0
vae/config.json
CHANGED
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@@ -21,6 +21,7 @@
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| 21 |
"norm_num_groups": 32,
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"out_channels": 3,
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"sample_size": 768,
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"up_block_types": [
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"UpDecoderBlock2D",
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"UpDecoderBlock2D",
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| 21 |
"norm_num_groups": 32,
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"out_channels": 3,
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"sample_size": 768,
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+
"scaling_factor": 0.18215,
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"up_block_types": [
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"UpDecoderBlock2D",
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"UpDecoderBlock2D",
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