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impactframes/QWQCoder - GGUF

This repo contains GGUF format model files for impactframes/QWQCoder.

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
QWQCoder-Q2_K.gguf Q2_K 6.607 GB smallest, significant quality loss - not recommended for most purposes
QWQCoder-Q3_K_S.gguf Q3_K_S 7.686 GB very small, high quality loss
QWQCoder-Q3_K_M.gguf Q3_K_M 8.458 GB very small, high quality loss
QWQCoder-Q3_K_L.gguf Q3_K_L 9.113 GB small, substantial quality loss
QWQCoder-Q4_0.gguf Q4_0 9.861 GB legacy; small, very high quality loss - prefer using Q3_K_M
QWQCoder-Q4_K_S.gguf Q4_K_S 9.935 GB small, greater quality loss
QWQCoder-Q4_K_M.gguf Q4_K_M 10.467 GB medium, balanced quality - recommended
QWQCoder-Q5_0.gguf Q5_0 11.909 GB legacy; medium, balanced quality - prefer using Q4_K_M
QWQCoder-Q5_K_S.gguf Q5_K_S 11.909 GB large, low quality loss - recommended
QWQCoder-Q5_K_M.gguf Q5_K_M 12.221 GB large, very low quality loss - recommended
QWQCoder-Q6_K.gguf Q6_K 14.085 GB very large, extremely low quality loss
QWQCoder-Q8_0.gguf Q8_0 18.241 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/QWQCoder-GGUF --include "QWQCoder-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/QWQCoder-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
282
GGUF
Model size
17.2B params
Architecture
qwen2

2-bit

3-bit

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Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for tensorblock/QWQCoder-GGUF

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