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:
- 80d52ffa42610904c1dd16ac503f42e750e8a48e6f318f4292896cb80d2ec313
- Size of remote file:
- 962 MB
- SHA256:
- 0b4ee04dcd8c60be62794b6e99438b6a9caf8cd063f11f69236b0652ad6e1dd9
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