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 pytorch_model.bin from wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner/resolve/main/pytorch_model.bin
436 MB
- Xet hash:
- 9b785d8c78555c263b48a39b54c5ceeb13cac07fc776b32933b7f6ea10ff7d65
- Size of remote file:
- 436 MB
- SHA256:
- f88369173bb2a2e2fcdbb3ac3b37d5a5482dd3c9606953dbeaf36b7e0da830ae
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