Instructions to use mbruton/spa_enpt_XLM-R with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbruton/spa_enpt_XLM-R with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbruton/spa_enpt_XLM-R")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbruton/spa_enpt_XLM-R") model = AutoModelForTokenClassification.from_pretrained("mbruton/spa_enpt_XLM-R", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 67da391b4674a2f3406772704b19438862cc48d3102a6c10af2405b1e41f2c5d
- Size of remote file:
- 3.5 kB
- SHA256:
- 7bdb8168f541f55141ebadb2957111c7e3a33318ba2ea1a68d683183673e8fcf
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