Instructions to use mbruton/spa_XLM-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/spa_XLM-R with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/spa_XLM-R")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/spa_XLM-R") model = AutoModelForTokenClassification.from_pretrained("mbruton/spa_XLM-R") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fffc894a37edeb793a16b9d79cff9f767929bdf42cb7306e8c8ddc04aaa5b748
- Size of remote file:
- 3.5 kB
- SHA256:
- 0ea9a039a2c97c351c3d1b0c9fc01c627f95bb8e4f82fced9a266ad3393875ed
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