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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c4c6de1f260e33554a212965cd8aeb339d5189f4e20b9c917a4005f8afc28227
- Size of remote file:
- 4.24 MB
- SHA256:
- 36eda917053139e75de97873a5432f095cec0b4d5621a45346ef3f26940f7d08
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