Instructions to use christofid/dabert-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use christofid/dabert-multi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="christofid/dabert-multi")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("christofid/dabert-multi") model = AutoModelForMaskedLM.from_pretrained("christofid/dabert-multi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7722db042cd85d0af0b41c43d69b4e3aab3c588a48cf95c52b468cf4af7ae39
- Size of remote file:
- 712 MB
- SHA256:
- 841c677bf2761a9e93ac10e649816a689238a7fb69789571148694b1c33feae4
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