Instructions to use fullstuck/transformers_resnet18_cifar100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fullstuck/transformers_resnet18_cifar100 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="fullstuck/transformers_resnet18_cifar100")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("fullstuck/transformers_resnet18_cifar100") model = AutoModel.from_pretrained("fullstuck/transformers_resnet18_cifar100", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from fullstuck/transformers_resnet18_cifar100: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/fullstuck/transformers_resnet18_cifar100/resolve/main/training_args.bin
- Command line
-
hf download hf://fullstuck/transformers_resnet18_cifar100/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/fullstuck/transformers_resnet18_cifar100/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- cd0d7736f4c0fc9c5757c968db1167ecc932da7fab78d117484e60c06a74bdf5
- Size of remote file:
- 4.73 kB
- SHA256:
- 832b7073fc0e254e46f2bc99e47c563c39c61c15f0b7cfe8550100513c6dec92
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