Instructions to use GleghornLab/copd_single with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GleghornLab/copd_single with Transformers:
# Load model directly from transformers import AutoTokenizer, BertForSentenceSimilarity tokenizer = AutoTokenizer.from_pretrained("GleghornLab/copd_single") model = BertForSentenceSimilarity.from_pretrained("GleghornLab/copd_single") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4aa619853c0354ec40c2eaa2709ce2eb83952f3263124544f86334402a28b7a
- Size of remote file:
- 440 MB
- SHA256:
- 84f64dcae316f6c0e1deb37e0635f65d2d9c4310f5ee2e630afec3a91813da7f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.