Instructions to use secilozksen/basecamp-cross-encoder-contriever with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use secilozksen/basecamp-cross-encoder-contriever with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="secilozksen/basecamp-cross-encoder-contriever")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("secilozksen/basecamp-cross-encoder-contriever") model = AutoModelForSequenceClassification.from_pretrained("secilozksen/basecamp-cross-encoder-contriever") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4af301dcfedc0451f9df8927ad44a84e190167ad63b6a299b8df8812bd55080c
- Size of remote file:
- 438 MB
- SHA256:
- 0c359c1030a3586ac220ad22c4589629d3c19f52ec22efc87cbcd644148d47bd
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