Instructions to use schrum2/MarioDiffusion-MLM-regular0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use schrum2/MarioDiffusion-MLM-regular0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("schrum2/MarioDiffusion-MLM-regular0", 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
Add missing comma
Browse files- model_index.json +1 -1
model_index.json
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"unet": [
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"diffusers",
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"UNet2DConditionModel"
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-
]
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"pipeline": "TextConditionalDDPMPipeline"
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}
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"unet": [
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"diffusers",
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"UNet2DConditionModel"
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],
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"pipeline": "TextConditionalDDPMPipeline"
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}
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