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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a20ad0f884c012a2e49542466fc2f5f5c608538a19d159f4625c4bd3ba7f12cb
- Size of remote file:
- 3.5 kB
- SHA256:
- 4316ad7da538db597cb2910839d0a3223975dab60336c26ca066dc0c4d61157c
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