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:
- c78f5b84ceec6da5bec3f46b3c905b5b71833da770228dd9f4d6ce57adb635f8
- Size of remote file:
- 6.76 MB
- SHA256:
- 4e2e867793ee546680c754a3ef13e6134405eff7a723b2803d316f96600b2317
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