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nvidia/Mistral-NeMo-Minitron-8B-Base - GGUF

This repo contains GGUF format model files for nvidia/Mistral-NeMo-Minitron-8B-Base.

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
Mistral-NeMo-Minitron-8B-Base-Q2_K.gguf Q2_K 3.104 GB smallest, significant quality loss - not recommended for most purposes
Mistral-NeMo-Minitron-8B-Base-Q3_K_S.gguf Q3_K_S 3.571 GB very small, high quality loss
Mistral-NeMo-Minitron-8B-Base-Q3_K_M.gguf Q3_K_M 3.920 GB very small, high quality loss
Mistral-NeMo-Minitron-8B-Base-Q3_K_L.gguf Q3_K_L 4.225 GB small, substantial quality loss
Mistral-NeMo-Minitron-8B-Base-Q4_0.gguf Q4_0 4.545 GB legacy; small, very high quality loss - prefer using Q3_K_M
Mistral-NeMo-Minitron-8B-Base-Q4_K_S.gguf Q4_K_S 4.575 GB small, greater quality loss
Mistral-NeMo-Minitron-8B-Base-Q4_K_M.gguf Q4_K_M 4.792 GB medium, balanced quality - recommended
Mistral-NeMo-Minitron-8B-Base-Q5_0.gguf Q5_0 5.462 GB legacy; medium, balanced quality - prefer using Q4_K_M
Mistral-NeMo-Minitron-8B-Base-Q5_K_S.gguf Q5_K_S 5.462 GB large, low quality loss - recommended
Mistral-NeMo-Minitron-8B-Base-Q5_K_M.gguf Q5_K_M 5.589 GB large, very low quality loss - recommended
Mistral-NeMo-Minitron-8B-Base-Q6_K.gguf Q6_K 6.436 GB very large, extremely low quality loss
Mistral-NeMo-Minitron-8B-Base-Q8_0.gguf Q8_0 8.334 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/Mistral-NeMo-Minitron-8B-Base-GGUF --include "Mistral-NeMo-Minitron-8B-Base-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/Mistral-NeMo-Minitron-8B-Base-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
327
GGUF
Model size
8.41B params
Architecture
llama

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8-bit

Inference API
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