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:
- fef4b00f7ce6403554ec0ddf36192caebf5cf70a4a56ebe684dd4024cae54a72
- Size of remote file:
- 2.22 GB
- SHA256:
- e61f35bd7651c584c19a9a00f0469d778bc83e10ef8132d040aba70f73510941
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