Instructions to use fusing/ddpm-cifar10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fusing/ddpm-cifar10 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fusing/ddpm-cifar10", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update model_index.json
Browse files- model_index.json +1 -0
model_index.json
CHANGED
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@@ -1,5 +1,6 @@
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{
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"_class_name": "DDPM",
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"noise_scheduler": [
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"diffusers",
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"GaussianDDPMScheduler"
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{
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"_class_name": "DDPM",
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"_module": "modeling_ddpm.py"
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"noise_scheduler": [
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"diffusers",
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"GaussianDDPMScheduler"
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