Instructions to use OpenSemShift/bert-c1-en-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenSemShift/bert-c1-en-de with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="OpenSemShift/bert-c1-en-de")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("OpenSemShift/bert-c1-en-de") model = AutoModelForMaskedLM.from_pretrained("OpenSemShift/bert-c1-en-de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b24a68917abe3abe110811d65704662128ccb72cbf515747fa3949eb359b7230
- Size of remote file:
- 714 MB
- SHA256:
- 66d651807fae178561c16b7da2dfc4b156bc79fc2697a9fe83eb23f6a799e731
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