Instructions to use mbruton/gal_pt_XLM-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/gal_pt_XLM-R with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/gal_pt_XLM-R")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/gal_pt_XLM-R") model = AutoModelForTokenClassification.from_pretrained("mbruton/gal_pt_XLM-R") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c193766bd105ec92eb01289b73386cde9d2e371f956d95fae7ec447ff3b2287e
- Size of remote file:
- 1.11 GB
- SHA256:
- 3bf9c02e3dff6bb6d8e6cfacb221d48414d460241514a13811dad4a71d652bd3
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