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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe86cec1108c09340f29009576f8e859244484a38ced14036d7733c1807e3799
- Size of remote file:
- 595 MB
- SHA256:
- d19b9cb78fe4adfcae45783ecba03814d614681d5a5b424a698966b95d7f0319
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