Instructions to use hf-tiny-model-private/tiny-random-SwitchTransformersModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-SwitchTransformersModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-SwitchTransformersModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-SwitchTransformersModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-SwitchTransformersModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9aadf0887fceda87e212b63b4f19ca8b7b3650a4fba90fe607e516bd4272e77
- Size of remote file:
- 4.49 MB
- SHA256:
- c59950e8522a223cdf74551e330a11046f5cfbadd49ae53b13f0c1b1ccc88f65
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