Instructions to use willmuldrew/foo-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use willmuldrew/foo-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="willmuldrew/foo-model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("willmuldrew/foo-model") model = AutoModelForMaskedLM.from_pretrained("willmuldrew/foo-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e6bf4cc1867939f8273f3c6a809c287c1ee2bf401c424ac356803991189796aa
- Size of remote file:
- 10.6 kB
- SHA256:
- e9a93edc665c5a9cf79f9c508261ee7cd66d0f4b01eca22dd0ade374d390e8a7
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