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)# 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/architecture.png from KBlueLeaf/TTVidT: direct link, hf CLI and curl.
- Browser
- Download file 280 kB
-
https://huggingface.co/KBlueLeaf/TTVidT/resolve/main/assets/architecture.png
- Command line
-
hf download hf://KBlueLeaf/TTVidT/assets/architecture.png
-
curl -L -o architecture.png https://huggingface.co/KBlueLeaf/TTVidT/resolve/main/assets/architecture.png
280 kB

- Xet hash:
- 69b4a2682c55cc5d2a0d47765d5e373ac55342fd1f11b947f19df3ba644bce70
- Size of remote file:
- 280 kB
- SHA256:
- dc88bbbe3ccf23f4bed9a6b2a1121985c3bd9dd507070cbe22feaa7e90722b79
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