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metadata
library_name: transformers
base_model: rasyosef/Mistral-NeMo-Minitron-8B-Chat
datasets:
  - teknium/OpenHermes-2.5
pipeline_tag: text-generation
license: other
license_name: nvidia-open-model-license
license_link: >-
  https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf
tags:
  - TensorBlock
  - GGUF
TensorBlock

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rasyosef/Mistral-NeMo-Minitron-8B-Chat - GGUF

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

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

Prompt template

<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Model file specification

Filename Quant type File Size Description
Mistral-NeMo-Minitron-8B-Chat-Q2_K.gguf Q2_K 3.333 GB smallest, significant quality loss - not recommended for most purposes
Mistral-NeMo-Minitron-8B-Chat-Q3_K_S.gguf Q3_K_S 3.834 GB very small, high quality loss
Mistral-NeMo-Minitron-8B-Chat-Q3_K_M.gguf Q3_K_M 4.209 GB very small, high quality loss
Mistral-NeMo-Minitron-8B-Chat-Q3_K_L.gguf Q3_K_L 4.537 GB small, substantial quality loss
Mistral-NeMo-Minitron-8B-Chat-Q4_0.gguf Q4_0 4.880 GB legacy; small, very high quality loss - prefer using Q3_K_M
Mistral-NeMo-Minitron-8B-Chat-Q4_K_S.gguf Q4_K_S 4.912 GB small, greater quality loss
Mistral-NeMo-Minitron-8B-Chat-Q4_K_M.gguf Q4_K_M 5.145 GB medium, balanced quality - recommended
Mistral-NeMo-Minitron-8B-Chat-Q5_0.gguf Q5_0 5.865 GB legacy; medium, balanced quality - prefer using Q4_K_M
Mistral-NeMo-Minitron-8B-Chat-Q5_K_S.gguf Q5_K_S 5.865 GB large, low quality loss - recommended
Mistral-NeMo-Minitron-8B-Chat-Q5_K_M.gguf Q5_K_M 6.001 GB large, very low quality loss - recommended
Mistral-NeMo-Minitron-8B-Chat-Q6_K.gguf Q6_K 6.911 GB very large, extremely low quality loss
Mistral-NeMo-Minitron-8B-Chat-Q8_0.gguf Q8_0 8.949 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-Chat-GGUF --include "Mistral-NeMo-Minitron-8B-Chat-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-Chat-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'