Instructions to use wietsedv/bert-base-dutch-cased-finetuned-sentiment 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-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wietsedv/bert-base-dutch-cased-finetuned-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wietsedv/bert-base-dutch-cased-finetuned-sentiment") model = AutoModelForSequenceClassification.from_pretrained("wietsedv/bert-base-dutch-cased-finetuned-sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6317bd29bcd7a248e68c75c34c5afcebd68c1eecc1b1fd5f6be93f8fa43f1ad
- Size of remote file:
- 436 MB
- SHA256:
- eed0181ebaff094439038c96f4f0fd61a22258085106e8cf55627410b19e73c3
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