Video Classification
Transformers
Safetensors
ttvidt
feature-extraction
video
video-representation-learning
self-supervised-learning
motion
temporal-modeling
dinov3
vision-transformer
custom_code
Eval Results (legacy)
Instructions to use KBlueLeaf/TTVidT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KBlueLeaf/TTVidT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="KBlueLeaf/TTVidT", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("KBlueLeaf/TTVidT", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download assets/overview.png from KBlueLeaf/TTVidT: direct link, hf CLI and curl.
- Browser
- Download file 2.52 MB
-
https://huggingface.co/KBlueLeaf/TTVidT/resolve/main/assets/overview.png
- Command line
-
hf download hf://KBlueLeaf/TTVidT/assets/overview.png
-
curl -L -o overview.png https://huggingface.co/KBlueLeaf/TTVidT/resolve/main/assets/overview.png
2.52 MB

- Xet hash:
- a6d20ec85c04249dbdd050331c654317485184133ca4bd12e8006c5f9284b843
- Size of remote file:
- 2.52 MB
- SHA256:
- 2ccb9be3afc8a270595d10746a9d40bc7801f0172ab8c348e2d2595884bca2fe
·
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