Instructions to use davanstrien/dataset-schema-task-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/dataset-schema-task-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="davanstrien/dataset-schema-task-classifier", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("davanstrien/dataset-schema-task-classifier", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("davanstrien/dataset-schema-task-classifier", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b41f7e415b20ca7aafd789402e77675ffaa8dc148894f36247d668857375e9bb
- Size of remote file:
- 1.42 GB
- SHA256:
- 834f8549cd6790992ec295591e2e798576e0ed5259c7fe23d3eae3b2525f1d3c
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