Instructions to use Arthur-Tsai/histv4_ftis_pretrain_tssp-smlm_0329 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arthur-Tsai/histv4_ftis_pretrain_tssp-smlm_0329 with Transformers:
# Load model directly from transformers import HiSenTrans model = HiSenTrans.from_pretrained("Arthur-Tsai/histv4_ftis_pretrain_tssp-smlm_0329", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94982d731a5384351b50f6288b0a3cb1ffbde3930d5da7c7930437b6e846fc38
- Size of remote file:
- 14.2 kB
- SHA256:
- 837c49157544195996ee306c12f4ae095deb8f14641418987a454ea77d02c41c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.