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MaziyarPanahi/Topxtral-4x7B-v0.1 - GGUF

This repo contains GGUF format model files for MaziyarPanahi/Topxtral-4x7B-v0.1.

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
Topxtral-4x7B-v0.1-Q2_K.gguf Q2_K 6.335 GB smallest, significant quality loss - not recommended for most purposes
Topxtral-4x7B-v0.1-Q3_K_S.gguf Q3_K_S 7.460 GB very small, high quality loss
Topxtral-4x7B-v0.1-Q3_K_M.gguf Q3_K_M 8.283 GB very small, high quality loss
Topxtral-4x7B-v0.1-Q3_K_L.gguf Q3_K_L 8.975 GB small, substantial quality loss
Topxtral-4x7B-v0.1-Q4_0.gguf Q4_0 9.734 GB legacy; small, very high quality loss - prefer using Q3_K_M
Topxtral-4x7B-v0.1-Q4_K_S.gguf Q4_K_S 9.818 GB small, greater quality loss
Topxtral-4x7B-v0.1-Q4_K_M.gguf Q4_K_M 10.427 GB medium, balanced quality - recommended
Topxtral-4x7B-v0.1-Q5_0.gguf Q5_0 11.875 GB legacy; medium, balanced quality - prefer using Q4_K_M
Topxtral-4x7B-v0.1-Q5_K_S.gguf Q5_K_S 11.875 GB large, low quality loss - recommended
Topxtral-4x7B-v0.1-Q5_K_M.gguf Q5_K_M 12.232 GB large, very low quality loss - recommended
Topxtral-4x7B-v0.1-Q6_K.gguf Q6_K 14.149 GB very large, extremely low quality loss
Topxtral-4x7B-v0.1-Q8_0.gguf Q8_0 18.325 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/Topxtral-4x7B-v0.1-GGUF --include "Topxtral-4x7B-v0.1-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/Topxtral-4x7B-v0.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
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GGUF
Model size
18.5B params
Architecture
llama

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