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:
- 5b199379b7d1c9b83468ab88ae5eb6bc5bb01156a0c72472a8bfeb7cb77bf524
- Size of remote file:
- 962 MB
- SHA256:
- 92b4eb4b41a4fdd29fa296ca969236da8c1c0c923dab34bfff0448484f2a8228
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