Instructions to use MirageML/lowpoly-game-building with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MirageML/lowpoly-game-building 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-game-building", 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
Commit ·
ad087d7
1
Parent(s): 4921be2
Add `scale_factor` to vae config. (#3)
Browse files- Add `scale_factor` to vae config. (19df831b9ca9051f87d3fab1c2605f108004bf59)
Co-authored-by: Suraj Patil <valhalla@users.noreply.huggingface.co>
- vae/config.json +1 -0
vae/config.json
CHANGED
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@@ -21,6 +21,7 @@
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"norm_num_groups": 32,
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"out_channels": 3,
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"sample_size": 512,
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"up_block_types": [
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"UpDecoderBlock2D",
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"UpDecoderBlock2D",
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"norm_num_groups": 32,
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"out_channels": 3,
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"sample_size": 512,
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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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