Instructions to use hf-internal-testing/tiny-random-FNetModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FNetModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-FNetModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FNetModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-FNetModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 377e421acc2d403d5777d75d2ad92b9300a1afe0377de03967290bb4135f3223
- Size of remote file:
- 4.23 MB
- SHA256:
- 5c1b648437207d58b5861409696b9cf1ea3283fa18a68b877bfb01ec89f1aa38
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