Instructions to use models-lab/modeling-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use models-lab/modeling-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="models-lab/modeling-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("models-lab/modeling-bert") model = AutoModelForMaskedLM.from_pretrained("models-lab/modeling-bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20f3226244b78d6776b4d67e847f0285cfb2a2a21d07401cc69e5a356712e1c6
- Size of remote file:
- 440 MB
- SHA256:
- cb2571b0f326b1848f328d74861c42c6d77e12c0ef2e9b70f888f9d59577895f
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