Instructions to use SparseCL/GTE-SparseCL-msmarco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SparseCL/GTE-SparseCL-msmarco with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import NewModelForCL model = NewModelForCL.from_pretrained("SparseCL/GTE-SparseCL-msmarco", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-4200/model.safetensors from SparseCL/GTE-SparseCL-msmarco: direct link, hf CLI and curl.
- Browser
- Download file 1.74 GB
-
https://huggingface.co/SparseCL/GTE-SparseCL-msmarco/resolve/main/checkpoint-4200/model.safetensors
- Command line
-
hf download hf://SparseCL/GTE-SparseCL-msmarco/checkpoint-4200/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/SparseCL/GTE-SparseCL-msmarco/resolve/main/checkpoint-4200/model.safetensors
1.74 GB
- Xet hash:
- 80dc6e35109cf99755680d361ad9559256e395fc9b0b032f1f5626ea1281a7ba
- Size of remote file:
- 1.74 GB
- SHA256:
- 8363ad9e6f06e6bc75da9a6a5524d4c6ec5fb6816afa269b962815cad8b19236
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