Instructions to use w139700701/BERT2DAb_H with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use w139700701/BERT2DAb_H with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="w139700701/BERT2DAb_H")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("w139700701/BERT2DAb_H") model = AutoModelForMaskedLM.from_pretrained("w139700701/BERT2DAb_H") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 464f48864a61d81468a38afb94d136567f216cdc34573287a0a374ea66aa87a9
- Size of remote file:
- 466 MB
- SHA256:
- 6d93063c1a4bb6b1439b97d5d1acd8aa0e1d47556278f2bcf21f86496107ec84
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