Instructions to use hf-internal-testing/tiny-random-FNetForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FNetForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-FNetForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FNetForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-FNetForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a7e13f2078125aa518bb080ce981eb60ba997e1529cb4fe077c05813918557f
- Size of remote file:
- 4.37 MB
- SHA256:
- 5d399a5f6ba9dc98b0f454b7126319408983232aab55f1dbab7a1f6ca87915ae
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