Instructions to use mbruton/gal_enpt_mBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/gal_enpt_mBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/gal_enpt_mBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/gal_enpt_mBERT") model = AutoModelForTokenClassification.from_pretrained("mbruton/gal_enpt_mBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3284a31cc48de03e76b6f175060b3e32c1cd2f82d1c8af8da37a46f0c4de14b8
- Size of remote file:
- 709 MB
- SHA256:
- b22f2bea072335c46e0ae230ab10efaa53a719b02791b16e94b20488bc4ae17c
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