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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from nbroad/muril-bigbird-large-1k: direct link, hf CLI and curl.
- Browser
- Download file 2.04 GB
-
https://huggingface.co/nbroad/muril-bigbird-large-1k/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://nbroad/muril-bigbird-large-1k/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/nbroad/muril-bigbird-large-1k/resolve/main/flax_model.msgpack
2.04 GB
- Xet hash:
- e28bdc9c2fe562e639f454d2a68b32c7558591ae6e6eb94320a6fb319bbeabec
- Size of remote file:
- 2.04 GB
- SHA256:
- 57da290c9f8ce4870e6dfb6de2cadd4b4ae3e428735f7b9a9f5a063a77360174
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