Instructions to use diffusers-internal-dev/private-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers-internal-dev/private-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers-internal-dev/private-model", 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
Update default sample size (#11)
Browse files- update default sample size (d926f260cdaa9c357a3deb95344a44021dcb9d91)
- transformer/config.json +1 -1
transformer/config.json
CHANGED
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@@ -11,5 +11,5 @@
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"out_channels": 16,
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"patch_size": 2,
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"pooled_projection_dim": 2048,
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| 14 |
-
"sample_size":
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| 15 |
}
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| 11 |
"out_channels": 16,
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| 12 |
"patch_size": 2,
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"pooled_projection_dim": 2048,
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+
"sample_size": 64
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}
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