Instructions to use hf-internal-testing/tiny-random-BigBirdForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BigBirdForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-BigBirdForMaskedLM", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BigBirdForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-BigBirdForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6eb37bd9f574990e41adcb789b1abbae6ac579a1a951049b0e3e6e1137974ee0
- Size of remote file:
- 6.75 MB
- SHA256:
- bed97cc94f4c9376265c616754267692c11d3d489c59191803ad280c869ead0f
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