Instructions to use wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner") model = AutoModelForTokenClassification.from_pretrained("wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner: direct link, hf CLI and curl.
- Browser
- Download file 434 MB
-
https://huggingface.co/wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner/resolve/main/flax_model.msgpack
434 MB
- Xet hash:
- d474d599e729878bf768037ea1f8cb09d8148ea118646a184e441624e2420890
- Size of remote file:
- 434 MB
- SHA256:
- 3d2d201a1c0fc5818fec18e10b7fd9bf5a2f931272e90f7ab3f8aeca9f9caf4e
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