Instructions to use immanuelpeter/C-RADIOv4-H with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use immanuelpeter/C-RADIOv4-H with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="immanuelpeter/C-RADIOv4-H")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("immanuelpeter/C-RADIOv4-H", device_map="auto") - Notebooks
- Google Colab
- Kaggle
C-RADIOv4-H
This repository packages the C-RADIOv4-H copy inside Nemotron 3 Nano Omni. It is not a clone of NVIDIA's standalone encoder nvidia/C-RADIOv4-H.
Contents
| File | Tensors | What it holds |
|---|---|---|
model.safetensors |
390 | RADIO Tower, extracted from Omni vision_model.* |
projector.safetensors |
3 | Omni mlp1 Projector |
config.json |
Vision-only RADIOModel config, with source and revision |
|
projector_config.json, projector.py |
Projector shapes and loader |
Architecture
| Component | Details |
|---|---|
| Tower | C-RADIOv4-H, 1280 hidden, patch size 16 |
| Token compression | InternVL v2 2x2 pixel shuffle, scale 0.5, no learned parameters |
Projector (mlp1) |
RMSNorm(5120), Linear(5120, 20480) no bias, SquaredReLU, Linear(20480, 2688) no bias |
| Extra | video_embedder Linear on the RADIO patch generator (2-frame tubelets) |
The standalone encoder does not ship this Omni Projector path. Omni SFT later stages train more than the Projector, so the ViT tensors can differ from nvidia/C-RADIOv4-H.
Usage
See examples/inference.py for image feature extraction.
AutoModel.from_pretrained on this repository will fail. The example builds RADIO
from the Omni vision_config (trust_remote_code=True) and loads the weights here.
Validation
The parity script
compares all 390 Tower tensors and three Projector tensors with the pinned Omni
parent using torch.equal. That is bit-identity with Omni vision_model.* and
mlp1.*, not with nvidia/C-RADIOv4-H.
Reproduction
The export script
reads vision_model.* (390 tensors) and mlp1.* (3 tensors) from shard 1 of
nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16. It removes the prefixes and
writes the original BF16 tensors.
Credits
NVIDIA released C-RADIOv4-H and Nemotron 3 Nano Omni. The Omni paper is arXiv:2604.24954.
License
NVIDIA Open Model Agreement, the same license as the source model.
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