Instructions to use SparseCL/BGE-SparseCL-arguana with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SparseCL/BGE-SparseCL-arguana with Transformers:
# Load model directly from transformers import AutoTokenizer, our_BertForCL tokenizer = AutoTokenizer.from_pretrained("SparseCL/BGE-SparseCL-arguana") model = our_BertForCL.from_pretrained("SparseCL/BGE-SparseCL-arguana") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f87ddae16954b8a51188e40e27f4394198a78767022cb28daa878953885c97be
- Size of remote file:
- 436 MB
- SHA256:
- 9bfc8399b76b6709e43654298a116c963952ab3651c25e7c8d11a6cda7e7aebb
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