Instructions to use mbruton/gal_ensp_XLM-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/gal_ensp_XLM-R with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/gal_ensp_XLM-R")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/gal_ensp_XLM-R") model = AutoModelForTokenClassification.from_pretrained("mbruton/gal_ensp_XLM-R", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8028546e54f54785ddb7344ee38efc98c8a7fb511d477f249b622c98437b140a
- Size of remote file:
- 3.5 kB
- SHA256:
- 2d5621949c04679a337d42240bf00bb3dcd12bd6983762011120c8214261928b
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