Instructions to use mbruton/gal_sp_XLM-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/gal_sp_XLM-R with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/gal_sp_XLM-R")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/gal_sp_XLM-R") model = AutoModelForTokenClassification.from_pretrained("mbruton/gal_sp_XLM-R") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ba1bc2037ac804030235f129ef29f3c1dff018c59dadcb99cb67d0d44cd165c
- Size of remote file:
- 14.5 kB
- SHA256:
- 067a3d9d4296a0274f96eb2257ae1d69ee29e64b2d5ab3e3a4d2593d403c095c
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