Instructions to use ajax-law/cross-encoder-binary-classification-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ajax-law/cross-encoder-binary-classification-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ajax-law/cross-encoder-binary-classification-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ajax-law/cross-encoder-binary-classification-base") model = AutoModelForSequenceClassification.from_pretrained("ajax-law/cross-encoder-binary-classification-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe72ce37072730c3edba1d5c0eaa055557f9ca7dbd598a060f931dc7d4c837cd
- Size of remote file:
- 499 MB
- SHA256:
- 18ac525a78c2d6839c3213b971df389951555ac689b193f3f6c832eac002c494
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