Instructions to use MirageML/lowpoly-office with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MirageML/lowpoly-office with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MirageML/lowpoly-office", 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 2'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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@@ -35,7 +35,7 @@
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| 35 |
"num_class_embeds": null,
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"only_cross_attention": false,
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"out_channels": 4,
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-
"sample_size":
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| 39 |
"up_block_types": [
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"UpBlock2D",
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"CrossAttnUpBlock2D",
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| 35 |
"num_class_embeds": null,
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| 36 |
"only_cross_attention": false,
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"out_channels": 4,
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| 38 |
+
"sample_size": 96,
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"up_block_types": [
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"UpBlock2D",
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"CrossAttnUpBlock2D",
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