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
File size: 168 Bytes
3e23fd4 | 1 2 3 4 5 6 7 | global_step = 1000000 loss = 1.5525091 masked_lm_accuracy = 0.67388266 masked_lm_loss = 1.5623554 next_sentence_accuracy = 0.99997187 next_sentence_loss = 7.288994e-05 |