Instructions to use mbruton/spa_pt_XLM-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/spa_pt_XLM-R with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/spa_pt_XLM-R")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/spa_pt_XLM-R") model = AutoModelForTokenClassification.from_pretrained("mbruton/spa_pt_XLM-R") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9906269b0d8d3689db748ce521931dd01a2dbb657fc616e8aef6b309ddbbeeb6
- Size of remote file:
- 3.5 kB
- SHA256:
- c9ce6e3aff5bb9c3a872e138f511783edd75f1b3aed17bd3f10e251e033b888a
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