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UnfilteredAI/Mia-001 - GGUF

This repo contains GGUF format model files for UnfilteredAI/Mia-001.

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
Mia-001-Q2_K.gguf Q2_K 0.052 GB smallest, significant quality loss - not recommended for most purposes
Mia-001-Q3_K_S.gguf Q3_K_S 0.057 GB very small, high quality loss
Mia-001-Q3_K_M.gguf Q3_K_M 0.062 GB very small, high quality loss
Mia-001-Q3_K_L.gguf Q3_K_L 0.066 GB small, substantial quality loss
Mia-001-Q4_0.gguf Q4_0 0.069 GB legacy; small, very high quality loss - prefer using Q3_K_M
Mia-001-Q4_K_S.gguf Q4_K_S 0.069 GB small, greater quality loss
Mia-001-Q4_K_M.gguf Q4_K_M 0.072 GB medium, balanced quality - recommended
Mia-001-Q5_0.gguf Q5_0 0.079 GB legacy; medium, balanced quality - prefer using Q4_K_M
Mia-001-Q5_K_S.gguf Q5_K_S 0.079 GB large, low quality loss - recommended
Mia-001-Q5_K_M.gguf Q5_K_M 0.081 GB large, very low quality loss - recommended
Mia-001-Q6_K.gguf Q6_K 0.091 GB very large, extremely low quality loss
Mia-001-Q8_0.gguf Q8_0 0.117 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/Mia-001-GGUF --include "Mia-001-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/Mia-001-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
34
GGUF
Model size
110M params
Architecture
llama

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Inference Examples
Unable to determine this model's library. Check the docs .

Model tree for tensorblock/Mia-001-GGUF

Quantized
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this model

Dataset used to train tensorblock/Mia-001-GGUF

Evaluation results