Instructions to use wietsedv/bert-base-dutch-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wietsedv/bert-base-dutch-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="wietsedv/bert-base-dutch-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("wietsedv/bert-base-dutch-cased") model = AutoModelForMaskedLM.from_pretrained("wietsedv/bert-base-dutch-cased") - Inference
- Notebooks
- Google Colab
- Kaggle
| { | |
| "do_lower_case": false, | |
| "unk_token": "[UNK]", | |
| "sep_token": "[SEP]", | |
| "pad_token": "[PAD]", | |
| "cls_token": "[CLS]", | |
| "mask_token": "[MASK]", | |
| "tokenize_chinese_chars": true, | |
| "strip_accents": null, | |
| "model_max_length": 512 | |
| } |