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")# 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:
- bf0f87b094eaa9a7e4a4129f82de0a72ea923f02546ac29adfc3f463b0758bb8
- Size of remote file:
- 6.76 MB
- SHA256:
- 081d4006d3f930aaf20f5c5e61b0459ab7a84597453bd7385405f95cc50dc6a4
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