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:
- 74c44806cc4bb558d4af5070ebbd82b27525053e7ff1ee7b690d05f9dfd366c0
- Size of remote file:
- 3.5 kB
- SHA256:
- 3a18d1c254f175fc584630799625e2e6bfeec2522ef70a979ca9ff0c48c92683
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