Instructions to use proycon/robbert-pos-cased-deepfrog-nld with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use proycon/robbert-pos-cased-deepfrog-nld with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="proycon/robbert-pos-cased-deepfrog-nld")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("proycon/robbert-pos-cased-deepfrog-nld") model = AutoModelForTokenClassification.from_pretrained("proycon/robbert-pos-cased-deepfrog-nld") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d55a1624722ccd1dd940154b985d5fec148d8ffe83e6a9d8b9bd4fc6af5cd0f6
- Size of remote file:
- 497 MB
- SHA256:
- 8b223f37deb8bc84cf1200e11a61ab018ccfd951b116d4b5af6612184993e485
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