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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8eeab32e1c967b9dc2c9342becafc794b47eded1481a5a621b5a7bad966c1c29
- Size of remote file:
- 436 MB
- SHA256:
- d95866acf9d64780d05f32e6226967f3bebea8573c9191d1a85733bce318bec1
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