Instructions to use ZinengTang/tvlt-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZinengTang/tvlt-base with Transformers:
# Load model directly from transformers import AutoModelForPreTraining model = AutoModelForPreTraining.from_pretrained("ZinengTang/tvlt-base", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f77eaa87ba6051a162181f3ff93eedab524c93b0d51b4c0a3738e810400758f0
- Size of remote file:
- 452 MB
- SHA256:
- 99416c68973fce2a0a7674d3b0872b3f2d26abbdb5182915d4b9a26ae6c053b0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.