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:
- 2f52f0403c97dd31080587503fbea08b25dd62ab6851f54521065b8cb58434d1
- Size of remote file:
- 962 MB
- SHA256:
- 9a27a51818882c80dc60c00a6758070d78bd85e45a66c91a5c31cf6f491516c7
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