Instructions to use proycon/robbert2-pos-cased-deepfrog-nld with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use proycon/robbert2-pos-cased-deepfrog-nld with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="proycon/robbert2-pos-cased-deepfrog-nld")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("proycon/robbert2-pos-cased-deepfrog-nld") model = AutoModelForTokenClassification.from_pretrained("proycon/robbert2-pos-cased-deepfrog-nld") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e66e2d216af74871eca803f7b67c6be77048734185806ad45aba82ab4c3e4ff8
- Size of remote file:
- 466 MB
- SHA256:
- 1c932b76acd16c1f34d736538b03003023706226b4197b2049c8f0085c5e5449
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