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Vikhrmodels/Vikhr-7B-instruct_0.4 - GGUF

This repo contains GGUF format model files for Vikhrmodels/Vikhr-7B-instruct_0.4.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Prompt template

<s><|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
Vikhr-7B-instruct_0.4-Q2_K.gguf Q2_K 2.740 GB smallest, significant quality loss - not recommended for most purposes
Vikhr-7B-instruct_0.4-Q3_K_S.gguf Q3_K_S 3.173 GB very small, high quality loss
Vikhr-7B-instruct_0.4-Q3_K_M.gguf Q3_K_M 3.503 GB very small, high quality loss
Vikhr-7B-instruct_0.4-Q3_K_L.gguf Q3_K_L 3.785 GB small, substantial quality loss
Vikhr-7B-instruct_0.4-Q4_0.gguf Q4_0 4.077 GB legacy; small, very high quality loss - prefer using Q3_K_M
Vikhr-7B-instruct_0.4-Q4_K_S.gguf Q4_K_S 4.106 GB small, greater quality loss
Vikhr-7B-instruct_0.4-Q4_K_M.gguf Q4_K_M 4.318 GB medium, balanced quality - recommended
Vikhr-7B-instruct_0.4-Q5_0.gguf Q5_0 4.927 GB legacy; medium, balanced quality - prefer using Q4_K_M
Vikhr-7B-instruct_0.4-Q5_K_S.gguf Q5_K_S 4.927 GB large, low quality loss - recommended
Vikhr-7B-instruct_0.4-Q5_K_M.gguf Q5_K_M 5.051 GB large, very low quality loss - recommended
Vikhr-7B-instruct_0.4-Q6_K.gguf Q6_K 5.830 GB very large, extremely low quality loss
Vikhr-7B-instruct_0.4-Q8_0.gguf Q8_0 7.550 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/Vikhr-7B-instruct_0.4-GGUF --include "Vikhr-7B-instruct_0.4-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/Vikhr-7B-instruct_0.4-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
207
GGUF
Model size
7.63B params
Architecture
llama

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Inference API
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