Instructions to use hucruz/datos-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hucruz/datos-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hucruz/datos-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hucruz/datos-ner") model = AutoModelForTokenClassification.from_pretrained("hucruz/datos-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 86192fcb7c5960cac55d7bf0984ddea55ff24ede3d261ebe88d41efa661d1018
- Size of remote file:
- 3.52 kB
- SHA256:
- 206005f06ba2ab1e5dba300ad172f1ae433faac8a4254bfd3d216ac7b2a1f9a5
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