Instructions to use OpenSemShift/bert-c2-en-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenSemShift/bert-c2-en-de with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="OpenSemShift/bert-c2-en-de")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("OpenSemShift/bert-c2-en-de") model = AutoModelForMaskedLM.from_pretrained("OpenSemShift/bert-c2-en-de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f8dbc180520536e5b0286e6ad40e9822bcacb68f92cc66c4249cd3e71e81d03d
- Size of remote file:
- 714 MB
- SHA256:
- 58c52a23188ae6c9f0ce42253cb7122d8df70d3fdf1b074db3fa4fc87ed84b0d
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