Instructions to use keonju/classificationmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keonju/classificationmodel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="keonju/classificationmodel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("keonju/classificationmodel") model = AutoModelForSequenceClassification.from_pretrained("keonju/classificationmodel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a642ae0df46ce994ed9b0de9dec31ae3d1774f2c1414b83bb8cd5ff2cd532ff2
- Size of remote file:
- 3.9 kB
- SHA256:
- 4266b123ac690a68b559e877e605130a568527da55ac1d84668a3cbda12e361a
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