Instructions to use WRHC/EfficientVideoAgent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WRHC/EfficientVideoAgent with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("WRHC/EfficientVideoAgent") model = AutoModelForImageTextToText.from_pretrained("WRHC/EfficientVideoAgent") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 0c65b33d85db8eb4d3362b01957c4d797f666c9daf256dd996bed335c266303b
- Size of remote file:
- 1.17 MB
- SHA256:
- bb6a723e8d9863a293fd7d2bdd8ea8e994ba146598f947e6fb9c95ed2b44d5e4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.