Instructions to use fusing/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fusing/test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fusing/test", 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
Correct `sample_size` of Stable Diffusion 1's unet to have correct width and height default
#1
by patrickvonplaten - opened
- unet/config.json +1 -1
unet/config.json
CHANGED
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@@ -26,7 +26,7 @@
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| 26 |
"norm_eps": 1e-05,
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| 27 |
"norm_num_groups": 32,
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| 28 |
"out_channels": 4,
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| 29 |
-
"sample_size":
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| 30 |
"up_block_types": [
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"UpBlock2D",
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"CrossAttnUpBlock2D",
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| 26 |
"norm_eps": 1e-05,
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| 27 |
"norm_num_groups": 32,
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| 28 |
"out_channels": 4,
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| 29 |
+
"sample_size": 64,
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| 30 |
"up_block_types": [
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"UpBlock2D",
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| 32 |
"CrossAttnUpBlock2D",
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