Instructions to use Arthur-Tsai/ht-stmini-cls-v5_ftis_noPretrain_tdso-smlo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arthur-Tsai/ht-stmini-cls-v5_ftis_noPretrain_tdso-smlo with Transformers:
# Load model directly from transformers import HiTrans model = HiTrans.from_pretrained("Arthur-Tsai/ht-stmini-cls-v5_ftis_noPretrain_tdso-smlo", dtype="auto") - Notebooks
- Google Colab
- Kaggle
ht-stmini-cls-v5_ftis_noPretrain_tdso-smlo / runs /0-sample_rate=0.2 /events.out.tfevents.1742912227.luna.609863.0
- Xet hash:
- e94f33c32c4358735f3b072767f279ec524a16b42a93ff435867df73f59e43ce
- Size of remote file:
- 232 kB
- SHA256:
- f33f93810d1bbfc0fe66d510dafbd7358b026af05fba41a4908d272cb3a360e1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.