Instructions to use mbruton/gal_ensp_mBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/gal_ensp_mBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/gal_ensp_mBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/gal_ensp_mBERT") model = AutoModelForTokenClassification.from_pretrained("mbruton/gal_ensp_mBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c954503400a080bf8098666f28f01dc9c4c40a8b72b12eab855e71541d866e6c
- Size of remote file:
- 14.5 kB
- SHA256:
- 478142f0fbeb50d21dde010322218069e75aaefea35c551e692fea734dd91394
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