Instructions to use davanstrien/datacard_to_task with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/datacard_to_task with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="davanstrien/datacard_to_task")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("davanstrien/datacard_to_task") model = AutoModelForSequenceClassification.from_pretrained("davanstrien/datacard_to_task") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d8a2fad132948db498c584c65de7b3bad0d8c4d47065bb31fea10849140eb5f0
- Size of remote file:
- 595 MB
- SHA256:
- c94785ac11a1621f764d660e97b1e62566e3330b4a55d5e78ac7b8e22678526b
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