Instructions to use RobinWZQ/backdoor_cat2dog with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RobinWZQ/backdoor_cat2dog with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("RobinWZQ/backdoor_cat2dog", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download text_encoder/pytorch_model.bin from RobinWZQ/backdoor_cat2dog: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/RobinWZQ/backdoor_cat2dog/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://RobinWZQ/backdoor_cat2dog/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/RobinWZQ/backdoor_cat2dog/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- ef40db4ab160692fba9d1675a9b677d92643f1bf10fb415b989f1144218092cb
- Size of remote file:
- 492 MB
- SHA256:
- 0bec13458ca963c1ba065e88f4f0cc3eb00d5d7397c5f8563ef0624ed9f8f9b9
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