Instructions to use w139700701/BERT2DAb_L with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use w139700701/BERT2DAb_L with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="w139700701/BERT2DAb_L")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("w139700701/BERT2DAb_L") model = AutoModelForMaskedLM.from_pretrained("w139700701/BERT2DAb_L") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0905540250a9f8a7cbb5e7d2279088bd266476c02eeeb86a0b0b738a4d3b6409
- Size of remote file:
- 466 MB
- SHA256:
- 3fdc794124cba213da036be538e9822b1364694a8f5367278f3d7cfcf809a676
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