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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 031e044c7b4b9b0eca0352a4d563d5fa4cc116f8c662f39db5e2ac10884f830b
- Size of remote file:
- 1.58 kB
- SHA256:
- 5ca7d585eea67c9effcd8b5b2d1f89ce3434d47fc16371fb773d32e37dc4810e
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