Image Classification
PyTorch
Safetensors
GGUF
MLX
compact_quality_net
video-quality-assessment
image-quality-assessment
knowledge-distillation
quantization
candle
kornia
robotics
first-person-video
Instructions to use shubhxho/video-benchmark-compact-quality with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use shubhxho/video-benchmark-compact-quality with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir video-benchmark-compact-quality shubhxho/video-benchmark-compact-quality
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat

- Xet hash:
- d571a1c812d0d1abf75120779791e5e72ac9b5e488aa528bae6a2008826f471e
- Size of remote file:
- 498 kB
- SHA256:
- d354937c142f16a21cd0939cba2b1143d5eedd25bbc7067e728b7ae2fbb486fd
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