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 env.py from KBlueLeaf/TTVidT: direct link, hf CLI and curl.
- Browser
- Download file 124 Bytes
-
https://huggingface.co/KBlueLeaf/TTVidT/resolve/main/env.py
- Command line
-
hf download hf://KBlueLeaf/TTVidT/env.py
-
curl -L -o env.py https://huggingface.co/KBlueLeaf/TTVidT/resolve/main/env.py
124 Bytes
| import os | |
| TORCH_COMPILE = os.environ.get("TORCH_COMPILE", "1") == "1" | |
| COMPILE_KWARG = {"mode": "default", "dynamic": False} | |