Instructions to use CAMeL-Lab/camelbert-msa-zaebuc-ged-13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CAMeL-Lab/camelbert-msa-zaebuc-ged-13 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="CAMeL-Lab/camelbert-msa-zaebuc-ged-13")# Load model directly from transformers import AutoTokenizer, BertForTokenClassificationSingleLabel tokenizer = AutoTokenizer.from_pretrained("CAMeL-Lab/camelbert-msa-zaebuc-ged-13") model = BertForTokenClassificationSingleLabel.from_pretrained("CAMeL-Lab/camelbert-msa-zaebuc-ged-13") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f69d8d073b99e9bb8442336256dc75f9273559b924282ed27bfea71cb74aad5e
- Size of remote file:
- 434 MB
- SHA256:
- fd1b45128bea890a56046fd27d9d3e4874b1ddae64c78ec05fb855617d9d1d72
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