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:
- 39c00fbe11afb7e6b5ecc3fa4f9c25e5a943e226f8cf1aff4dbcecaa886c0853
- Size of remote file:
- 127 MB
- SHA256:
- f28ce8bc9dc600fb8de29e9c331f82207c9af3ad65d452636219ee52d1b30c28
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.