Instructions to use sck/test-glue-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sck/test-glue-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sck/test-glue-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sck/test-glue-classification") model = AutoModelForSequenceClassification.from_pretrained("sck/test-glue-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f74b714482b58b8719a5aa5f47448dea66c0cef9cf4008057a44a27e9a10ee92
- Size of remote file:
- 438 MB
- SHA256:
- f27919f5d127350d463a0a62ea91a15a6894c1bfe89f7d9da997f903e66afe42
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