Any-to-Any
Transformers
Safetensors
English
NemotronH_Nano_Omni_Reasoning_V3
feature-extraction
nvidia
nemotron
multimodal
quantized
4-bit precision
int4
custom_code
compressed-tensors
Instructions to use drawais/Nemotron-3-Nano-Omni-30B-A3B-W4A16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use drawais/Nemotron-3-Nano-Omni-30B-A3B-W4A16 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("drawais/Nemotron-3-Nano-Omni-30B-A3B-W4A16", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c50b024d1e486d2768f584ed225e56fb036456d2617389b4ea099b4fdd085590
- Size of remote file:
- 1.41 GB
- SHA256:
- cfb6c732633417422013aaab3f105040d144788424fc92644a1b4a5401bb6565
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