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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a76e83e1adab46b1e877632203ef10ac8d0fc77a95e567645728bbb8534145cd
- Size of remote file:
- 4.47 MB
- SHA256:
- 040aa156c44d3ac2f8442212a959c57fac40e15b0d570782107538fd98da130c
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