Instructions to use nbroad/muril-bigbird-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nbroad/muril-bigbird-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nbroad/muril-bigbird-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nbroad/muril-bigbird-base") model = AutoModelForMaskedLM.from_pretrained("nbroad/muril-bigbird-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45c86eb2c9004cc6c5e50d42b9b335c36012f0d92335e71422de1d4774e00afc
- Size of remote file:
- 962 MB
- SHA256:
- ee88317b8117ad2298f4690bf5c4986bdc07f35f656802d692d990250b6708cd
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