Instructions to use CYONG/slv-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CYONG/slv-text-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CYONG/slv-text-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CYONG/slv-text-classification") model = AutoModelForSequenceClassification.from_pretrained("CYONG/slv-text-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33d6820e29400165f5c3ed61d4e47bb5a81f4286149533cf13c687317bffb10f
- Size of remote file:
- 55.1 MB
- SHA256:
- 405f490cc74c29d517b626c98a4b8977cfcdd44720d696cc97c10a216201a561
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