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:
- 01c34f55b1096dbb5154fd3b1672aeb5666a3950ba7b7b919948b4ab0842c081
- Size of remote file:
- 267 MB
- SHA256:
- 4002bd29a018c75f63c4ddb087b2d8eea4745f72f2c4bc32b4794828c904acde
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