Instructions to use GroNLP/bert_dutch_base_abusive_language with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GroNLP/bert_dutch_base_abusive_language with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GroNLP/bert_dutch_base_abusive_language")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GroNLP/bert_dutch_base_abusive_language") model = AutoModelForSequenceClassification.from_pretrained("GroNLP/bert_dutch_base_abusive_language", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from GroNLP/bert_dutch_base_abusive_language: direct link, hf CLI and curl.
- Browser
- Download file 437 MB
-
https://huggingface.co/GroNLP/bert_dutch_base_abusive_language/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://GroNLP/bert_dutch_base_abusive_language/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/GroNLP/bert_dutch_base_abusive_language/resolve/main/pytorch_model.bin
437 MB
- Xet hash:
- 09c31c47badfdc25be0c71a9663a07e93193dacbf5728583561a758d083f56bc
- Size of remote file:
- 437 MB
- SHA256:
- 97c4bb63b01b3aaf261ffdb123f2f420a3d8eb5bc779cc3e9447d7a546a8d894
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