Instructions to use garNER/bert-base-multilingual-cased-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use garNER/bert-base-multilingual-cased-de with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="garNER/bert-base-multilingual-cased-de")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("garNER/bert-base-multilingual-cased-de") model = AutoModelForTokenClassification.from_pretrained("garNER/bert-base-multilingual-cased-de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3698974960c8ccf976e6302df9c4b1d69716151aa87af76a58bc886d83f4372
- Size of remote file:
- 3.52 kB
- SHA256:
- ca01008996b0f073649c0986572d22c030b8633c3b572d84ea9a6989294abd3b
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