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:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForPreTraining model = AutoModelForPreTraining.from_pretrained("ZinengTang/tvlt-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from ZinengTang/tvlt-base: direct link, hf CLI and curl.
- Browser
- Download file 308 Bytes
-
https://huggingface.co/ZinengTang/tvlt-base/resolve/refs%2Fpr%2F1/preprocessor_config.json
- Command line
-
hf download hf://ZinengTang/tvlt-base@refs/pr/1/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/ZinengTang/tvlt-base/resolve/refs%2Fpr%2F1/preprocessor_config.json
308 Bytes
| { | |
| "do_resize": true, | |
| "size": {"shortest_edge": 224}, | |
| "do_center_crop": true, | |
| "crop_size": {"height": 224, "width": 224}, | |
| "resample": 2, | |
| "do_rescale": true, | |
| "rescale_factor": 0.00392156862745098, | |
| "do_normalize": true, | |
| "image_mean": [0.5, 0.5, 0.5], | |
| "image_std": [0.5, 0.5, 0.5] | |
| } |