Model Overview
Description:
This model performs visual feature extraction. For instance, RADIO generates image embeddings that can be used by a downstream model to classify images.
This model is for research and development only.
License/Terms of Use
References:
Model Architecture:
Architecture Type: Neural Network
Network Architecture: Vision Transformer
Input:
Input Type(s): Image
Input Format(s): Red, Green, Blue (RGB)
Input Parameters: Two Dimensional (2D)
Other Properties Related to Input: Image resolutions up to 2048x2028 in increments of 16 pixels
Output:
Output Type(s): Embeddings
Output Format: Tensor
Output Parameters: 2D
Other Properties Related to Output: Downstream model required to leverage image features
Software Integration:
Runtime Engine(s):
- TAO- 24.10
Supported Hardware Microarchitecture Compatibility:
- NVIDIA Ampere
- NVIDIA Blackwell
- NVIDIA Jetson
- NVIDIA Hopper
- NVIDIA Lovelace
- NVIDIA Pascal
- NVIDIA Turing
- NVIDIA Volta
[Preferred/Supported] Operating System(s):
- Linux
- Linux 4 Tegra
- QNX
- Windows
Model Version(s):
C-RADIO.
Link: https://huggingface.co/nvidia/C-RADIO
Training, Testing, and Evaluation Datasets:
Training Dataset:
NV-CC-Img-Text-Dataset
** Data Collection Method by dataset
- Automated
** Labeling Method by dataset - Not Applicable (no labels are needed)
Properties: 700 Million Images
Evaluation Dataset:
Link: ImageNet
** Data Collection Method by dataset
- Automated
** Labeling Method by dataset - Human
Properties: This dataset spans 1000 object classes and contains 1,281,167 training images, 50,000 validation images and 100,000 test images.
Inference:
Engine: PyTorch
Test Hardware: A100
Ethical Considerations (For NVIDIA Models Only):
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