Instructions to use hf-tiny-model-private/tiny-random-BigBirdForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-BigBirdForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-tiny-model-private/tiny-random-BigBirdForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-BigBirdForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-BigBirdForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad618aa85a687bcae0583e53f311093b38b0d4d00d3d0cfdf8e3be0e9e217dc0
- Size of remote file:
- 6.75 MB
- SHA256:
- 8724bbf60d07d352ee63a9ad5fa4d0af724ea9e1324789805b2a1a00791055f0
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