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:
- 07e06827ea06cb4bc6281ece534ce3cd1c5e795fc6d6286658c9a4e44ff00552
- Size of remote file:
- 1.36 GB
- SHA256:
- 43b70b617eb614a07c1c027e64a9016bbe6a29af10faf7a44dc7c89d0abbf240
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