Instructions to use gijsdanoe/bertje_dva with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gijsdanoe/bertje_dva with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gijsdanoe/bertje_dva")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gijsdanoe/bertje_dva") model = AutoModelForSequenceClassification.from_pretrained("gijsdanoe/bertje_dva") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf2e77285e2d60237fa8022e2c972a9fc460fdd5c20bcd2e7361f26a26822080
- Size of remote file:
- 437 MB
- SHA256:
- d940be5548d570dd7fa7e10a63d7cb890c7a778944b5c96be01368a771a3b49a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.