Instructions to use nbroad/muril-bigbird-large-1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nbroad/muril-bigbird-large-1k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nbroad/muril-bigbird-large-1k")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nbroad/muril-bigbird-large-1k") model = AutoModelForMaskedLM.from_pretrained("nbroad/muril-bigbird-large-1k") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e28bdc9c2fe562e639f454d2a68b32c7558591ae6e6eb94320a6fb319bbeabec
- Size of remote file:
- 2.04 GB
- SHA256:
- 57da290c9f8ce4870e6dfb6de2cadd4b4ae3e428735f7b9a9f5a063a77360174
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