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-2800/tokenizer.json from SparseCL/GTE-SparseCL-msmarco: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/SparseCL/GTE-SparseCL-msmarco/resolve/main/checkpoint-2800/tokenizer.json
- Command line
-
hf download hf://SparseCL/GTE-SparseCL-msmarco/checkpoint-2800/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/SparseCL/GTE-SparseCL-msmarco/resolve/main/checkpoint-2800/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.