| Instantiate a pipeline for video classification with your model, and pass your video to it: | |
| from transformers import pipeline | |
| video_cls = pipeline(model="my_awesome_video_cls_model") | |
| video_cls("https://huggingface.co/datasets/sayakpaul/ucf101-subset/resolve/main/v_BasketballDunk_g14_c06.avi") | |
| [{'score': 0.9272987842559814, 'label': 'BasketballDunk'}, | |
| {'score': 0.017777055501937866, 'label': 'BabyCrawling'}, | |
| {'score': 0.01663011871278286, 'label': 'BalanceBeam'}, | |
| {'score': 0.009560945443809032, 'label': 'BandMarching'}, | |
| {'score': 0.0068979403004050255, 'label': 'BaseballPitch'}] | |
| You can also manually replicate the results of the pipeline if you'd like. |