Instructions to use mbruton/spa_en_XLM-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/spa_en_XLM-R with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/spa_en_XLM-R")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/spa_en_XLM-R") model = AutoModelForTokenClassification.from_pretrained("mbruton/spa_en_XLM-R") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8692f2fca58abd783f1f3fde60c1d50949c6d922bf540f2d7538bca672a271c4
- Size of remote file:
- 2.22 GB
- SHA256:
- d37fabdd87b8ba617ccaf6da4054557c638d726be03efd1d463589469053d871
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