# 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
[License](https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf)

## References:
[Paper](https://arxiv.org/abs/2312.06709)

## Model Architecture:
**Architecture Type:** Neural Network  <br>
**Network Architecture:** Vision Transformer <br>

## Input:
**Input Type(s):** Image <br>
**Input Format(s):** Red, Green, Blue (RGB) <br>
**Input Parameters:** Two Dimensional (2D) <br>
**Other Properties Related to Input:** Image resolutions up to 2048x2028 in increments of 16 pixels <br>

## Output:
**Output Type(s):** Embeddings <br>
**Output Format:** Tensor <br>
**Output Parameters:** 2D <br>
**Other Properties Related to Output:** Downstream model required to leverage image features <br>

## Software Integration:
**Runtime Engine(s):**
* TAO- 24.10 <br>

**Supported Hardware Microarchitecture Compatibility:** <br>
* NVIDIA Ampere <br>
* NVIDIA Blackwell <br>
* NVIDIA Jetson  <br>
* NVIDIA Hopper <br>
* NVIDIA Lovelace <br>
* NVIDIA Pascal <br>
* NVIDIA Turing <br>
* NVIDIA Volta <br>

**[Preferred/Supported] Operating System(s):** <br>
* 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  <br>
** Data Collection Method by dataset <br>
* Automated <br>
** Labeling Method by dataset <br>
* Not Applicable (no labels are needed) <br>
**Properties:** 700 Million Images <br>

## Evaluation Dataset:
**Link:** [ImageNet](https://www.image-net.org/)  <br>
** Data Collection Method by dataset <br>
* Automated <br>
** Labeling Method by dataset <br>
* Human <br>

**Properties:** This dataset spans 1000 object classes and contains 1,281,167 training images, 50,000 validation images and 100,000 test images.<br>

## Inference:
**Engine:** PyTorch <br>
**Test Hardware:** A100 <br>

## Ethical Considerations (For NVIDIA Models Only):
NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications.  When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.

Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).