Instructions to use webis/sparse-cross-encoder-4-512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use webis/sparse-cross-encoder-4-512 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="webis/sparse-cross-encoder-4-512")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("webis/sparse-cross-encoder-4-512") model = AutoModelForSequenceClassification.from_pretrained("webis/sparse-cross-encoder-4-512") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc6912210bd39540ddf4649aa54e509d4ef732b6df360e1d0a9a342060a6da97
- Size of remote file:
- 90.9 MB
- SHA256:
- 58d33775f80a8e1da0950618fb7929eb4c928186223296c74e3e3fa457a83826
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