Instructions to use mbruton/gal_XLM-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/gal_XLM-R with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/gal_XLM-R")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/gal_XLM-R") model = AutoModelForTokenClassification.from_pretrained("mbruton/gal_XLM-R") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a75c30391bc572d4c408dceeef63a2c6f844353c0bc6c01001d7e74b2871d18
- Size of remote file:
- 3.5 kB
- SHA256:
- 148d1a0e1c0b8b47d12a8fa1553e05099d6efd850cb2de1555d9a2878f796025
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