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thhaus/nemotron3-8b - GGUF

This repo contains GGUF format model files for thhaus/nemotron3-8b.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Prompt template


Model file specification

Filename Quant type File Size Description
nemotron3-8b-Q2_K.gguf Q2_K 3.654 GB smallest, significant quality loss - not recommended for most purposes
nemotron3-8b-Q3_K_S.gguf Q3_K_S 4.087 GB very small, high quality loss
nemotron3-8b-Q3_K_M.gguf Q3_K_M 4.536 GB very small, high quality loss
nemotron3-8b-Q3_K_L.gguf Q3_K_L 4.918 GB small, substantial quality loss
nemotron3-8b-Q4_0.gguf Q4_0 5.082 GB legacy; small, very high quality loss - prefer using Q3_K_M
nemotron3-8b-Q4_K_S.gguf Q4_K_S 5.124 GB small, greater quality loss
nemotron3-8b-Q4_K_M.gguf Q4_K_M 5.428 GB medium, balanced quality - recommended
nemotron3-8b-Q5_0.gguf Q5_0 6.019 GB legacy; medium, balanced quality - prefer using Q4_K_M
nemotron3-8b-Q5_K_S.gguf Q5_K_S 6.019 GB large, low quality loss - recommended
nemotron3-8b-Q5_K_M.gguf Q5_K_M 6.197 GB large, very low quality loss - recommended
nemotron3-8b-Q6_K.gguf Q6_K 7.014 GB very large, extremely low quality loss
nemotron3-8b-Q8_0.gguf Q8_0 9.082 GB very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/nemotron3-8b-GGUF --include "nemotron3-8b-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/nemotron3-8b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
288
GGUF
Model size
8.54B params
Architecture
nemotron

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