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:
- 7f9517baff5bce97a3e8254a744f799a877fc31b0ae8103a0f2933e7844575c0
- Size of remote file:
- 3.44 kB
- SHA256:
- 7f1eed92dcb7bd80c598326878cb384bf0a109bb94ecbcabc6422d1450fb342b
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