Instructions to use scikit-bio/tmvec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scikit-bio/tmvec with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("scikit-bio/tmvec", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5bae5e4885523a7ffcc764ddc21492d1de6fc545d159f64f503a3ba90b306eff
- Size of remote file:
- 69.3 MB
- SHA256:
- 3dfb23e90777983d3b7a6bbfe857971e825178d499608b6b97f2508fbdec9536
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.