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:
- 89c9cf98451b6e4098e570f1da73ecfb1086a7d3cb3b1e6b909412d243bb8208
- Size of remote file:
- 3.5 kB
- SHA256:
- cb3ea1aa29eae0aeed5148d612afffd503be132bf9b208cf0636249620f3c5af
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