Instructions to use reichenbach/switch-transformer-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use reichenbach/switch-transformer-classification with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy), and from_pretrained_keras was removed in huggingface_hub 1.0. # See https://github.com/keras-team/tf-keras for more details. # !pip install "huggingface_hub<1.0" tf_keras from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("reichenbach/switch-transformer-classification") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from reichenbach/switch-transformer-classification: direct link, hf CLI and curl.
- Browser
- Download file 1.15 MB
-
https://huggingface.co/reichenbach/switch-transformer-classification/resolve/main/saved_model.pb
- Command line
-
hf download hf://reichenbach/switch-transformer-classification/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/reichenbach/switch-transformer-classification/resolve/main/saved_model.pb
1.15 MB
- Xet hash:
- 2453b8f6c0fd20809692ecf4855f186a686d35a3be3cbbba714ca3261512b62e
- Size of remote file:
- 1.15 MB
- SHA256:
- 8c32d470b23153d8ab7a3228b32c5ec7e731ae600225ac09a7766cb64bbe4104
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