Instructions to use Tommidi/st_vit_trained-8epoch-ucf101-subset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tommidi/st_vit_trained-8epoch-ucf101-subset with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import ST_Vit model = ST_Vit.from_pretrained("Tommidi/st_vit_trained-8epoch-ucf101-subset", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download test_results.json from Tommidi/st_vit_trained-8epoch-ucf101-subset: direct link, hf CLI and curl.
- Browser
- Download file 203 Bytes
-
https://huggingface.co/Tommidi/st_vit_trained-8epoch-ucf101-subset/resolve/main/test_results.json
- Command line
-
hf download hf://Tommidi/st_vit_trained-8epoch-ucf101-subset/test_results.json
-
curl -L -o test_results.json https://huggingface.co/Tommidi/st_vit_trained-8epoch-ucf101-subset/resolve/main/test_results.json
203 Bytes
| { | |
| "epoch": 7.1, | |
| "eval_accuracy": 0.9733333333333334, | |
| "eval_loss": 0.06482689082622528, | |
| "eval_runtime": 274.5585, | |
| "eval_samples_per_second": 0.273, | |
| "eval_steps_per_second": 0.036 | |
| } |