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:
- 7d9eda92642185634b0f4f5d2f9a07b4d564ff1fc7f5c96835da204f26aadc15
- Size of remote file:
- 871 MB
- SHA256:
- 79221aab5de71b632a066a0a3b30101f57c410defa493d51072d4b7806598bf9
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