Instructions to use hf-internal-testing/tiny-random-SwitchTransformersModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SwitchTransformersModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-SwitchTransformersModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-SwitchTransformersModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-SwitchTransformersModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 40f9a92188f2c3e2ba4211e0395ffcd22bfca22b5e33f10d33b7939d5d05bb13
- Size of remote file:
- 4.49 MB
- SHA256:
- ab5dc7b5fea43a52d11f5f5d689837e64eb49d6243703eaa845e1c37662dfc83
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