Instructions to use mbruton/gal_enpt_XLM-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/gal_enpt_XLM-R with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/gal_enpt_XLM-R")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/gal_enpt_XLM-R") model = AutoModelForTokenClassification.from_pretrained("mbruton/gal_enpt_XLM-R") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f8bacd48a32f66b2817bafbf1754e9581b00d633ea7add5fe7abf33fc761460c
- Size of remote file:
- 2.22 GB
- SHA256:
- b3ec50b331c87a2c313f2c88e22bcd8a351c9521b7c8bcbb6c50f6c481f156b2
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