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vihangd/smartsolmix-4x10.7b-v1 - GGUF

This repo contains GGUF format model files for vihangd/smartsolmix-4x10.7b-v1.

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

Prompt template


Model file specification

Filename Quant type File Size Description
smartsolmix-4x10.7b-v1-Q2_K.gguf Q2_K 13.189 GB smallest, significant quality loss - not recommended for most purposes
smartsolmix-4x10.7b-v1-Q3_K_S.gguf Q3_K_S 15.568 GB very small, high quality loss
smartsolmix-4x10.7b-v1-Q3_K_M.gguf Q3_K_M 17.288 GB very small, high quality loss
smartsolmix-4x10.7b-v1-Q3_K_L.gguf Q3_K_L 18.734 GB small, substantial quality loss
smartsolmix-4x10.7b-v1-Q4_0.gguf Q4_0 20.345 GB legacy; small, very high quality loss - prefer using Q3_K_M
smartsolmix-4x10.7b-v1-Q4_K_S.gguf Q4_K_S 20.523 GB small, greater quality loss
smartsolmix-4x10.7b-v1-Q4_K_M.gguf Q4_K_M 21.824 GB medium, balanced quality - recommended
smartsolmix-4x10.7b-v1-Q5_0.gguf Q5_0 24.840 GB legacy; medium, balanced quality - prefer using Q4_K_M
smartsolmix-4x10.7b-v1-Q5_K_S.gguf Q5_K_S 24.840 GB large, low quality loss - recommended
smartsolmix-4x10.7b-v1-Q5_K_M.gguf Q5_K_M 25.603 GB large, very low quality loss - recommended
smartsolmix-4x10.7b-v1-Q6_K.gguf Q6_K 29.617 GB very large, extremely low quality loss
smartsolmix-4x10.7b-v1-Q8_0.gguf Q8_0 38.360 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/smartsolmix-4x10.7b-v1-GGUF --include "smartsolmix-4x10.7b-v1-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/smartsolmix-4x10.7b-v1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
177
GGUF
Model size
36.1B params
Architecture
llama

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Inference API
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