Instructions to use mbruton/gal_en_XLM-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/gal_en_XLM-R with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/gal_en_XLM-R")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/gal_en_XLM-R") model = AutoModelForTokenClassification.from_pretrained("mbruton/gal_en_XLM-R") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ebb5d43c331b50d30550d26f77c1746a1861333441ddb085124f8720cde014e
- Size of remote file:
- 623 Bytes
- SHA256:
- 265c7006548b2b66fb3cdd7eb5fc39bbc47df737153fea96dfb44973cb0cb1ce
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