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 /9-sample_rate=0.2 /events.out.tfevents.1745138587.yara2.3182472.0
- Xet hash:
- 326ac506ff906a57b9146321eebb268be390af1d6715eae03e5fb110387d1d49
- Size of remote file:
- 378 kB
- SHA256:
- 2fabef74f1930af9c73d71d669d86f06df7236efce1d7b879c90b36064ff7636
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.