Instructions to use wltjr1007/testsss with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wltjr1007/testsss with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="wltjr1007/testsss", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("wltjr1007/testsss", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload ConditionalUNet
Browse files- configuration_conditional_unet.py +1 -5
- model.safetensors +1 -1
configuration_conditional_unet.py
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self.encoder_rep = encoder_rep
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@classmethod
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def from_pretrained(cls, *args, **kwargs):
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**kwargs
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super().__init__(**kwargs)
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self.encoder_rep = encoder_rep
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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oid sha256:3cbf9eb9ce0bb6ebf5117d63a53a5efc50040f4918ded8b837ca86163d83bc0e
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size 293858844
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