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:
- b5dee3df7a66f18c866c4d5ad727688289ab984a4496709d0b89ba1c8439a2aa
- Size of remote file:
- 1.11 GB
- SHA256:
- 3c3ed27f27193763719bfd990291d0a0424ffb5a0457f5f535c3d9607ce5cdb4
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