Instructions to use dccuchile/roberta-large-bne-finetuned-pos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dccuchile/roberta-large-bne-finetuned-pos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dccuchile/roberta-large-bne-finetuned-pos")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dccuchile/roberta-large-bne-finetuned-pos") model = AutoModelForTokenClassification.from_pretrained("dccuchile/roberta-large-bne-finetuned-pos") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c1220bac936ac9345f7615c0e5623bc5540fc1a38cda38cd728aba8f6358f77
- Size of remote file:
- 2.99 kB
- SHA256:
- 5a2ec57283b8a6c6a45f412f9fb0f2f79ac7e8a38c01249b1f09454831ac3ebd
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