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:
- ea688e3ed7da498d9d344979054df03a3f5f585db9c7653fc506e591fd564750
- Size of remote file:
- 4.03 kB
- SHA256:
- 6d10ee89fda81e9be235e963ae87e2712203d4d8f7f1e6bdd8189d8d69b8fff1
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