Nemotron-3-Nano-Omni-AEON-Ultimate-Uncensored — GGUF

🎯 GGUF Conversion of the original AEON-7/Nemotron-3-Nano-Omni-AEON-Ultimate-Uncensored-BF16

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📦 Files

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🧠 Model Architecture

Source Model

• Creator: AEON-7
• Original: Nemotron-3-Nano-Omni-AEON-Ultimate-Uncensored-BF16
• Base Architecture: NVIDIA NemotronH (Nemotron-3-Nano)

LLM Backbone — NemotronHForCausalLM

• Layers: 52 hybrid layers
• Hidden Size: 2,688
• MoE: 128 routed experts, 6 active per token, 1 shared expert
• Hybrid Pattern: MEMEM*EMEMEM*EMEMEM*EMEMEM*EMEMEM*EMEMEMEM*EMEMEMEME
  • M = Mamba2 (SSM)
  • E = Expert (Mixture of Experts)
  • * = Attention
• Context Length: 131,072 tokens
• Vocab Size: 131,072

Vision Encoder — ViT-Huge (RADIO v2.5)

• Layers: 32
• Hidden Size: 1,280
• Image Size: 512×512
• Patch Size: 16

Audio Encoder — Parakeet

• Layers: 24
• Hidden Size: 1,024
• Sample Rate: 16kHz

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🚀 Usage with llama.cpp

Text-Only Inference

./llama-cli \
  -m Nemotron-3-Nano-Omni-AEON-Uncensored-Q6_K.gguf \
  -p "Hello, how are you?" \
  -n 256

Vision (Image Understanding)

./llama-llava-cli \
  -m Nemotron-3-Nano-Omni-AEON-Uncensored-Q6_K.gguf \
  --mmproj mmproj-Nemotron-3-Nano-Omni-BF16.gguf \
  --image image.jpg \
  -p "Describe this image in detail."

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📝 Conversion Details

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🙏 Credits & Attribution

This is a GGUF conversion only. All model weights originate from:

💡 Note: This repo contains only GGUF format files converted from the original AEON-7 model. For the original PyTorch/SafeTensors weights, please visit the source model.

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⚠️ Disclaimer

This is an uncensored model. Use responsibly and in compliance with applicable laws and regulations.