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allura-org/GLM4-9B-Neon-v2 - GGUF

This repo contains GGUF format model files for allura-org/GLM4-9B-Neon-v2.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5753.

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Prompt template

[gMASK]<sop><|system|>
{system_prompt}<|user|>
{prompt}<|assistant|>

Model file specification

Filename Quant type File Size Description
GLM4-9B-Neon-v2-Q2_K.gguf Q2_K 4.006 GB smallest, significant quality loss - not recommended for most purposes
GLM4-9B-Neon-v2-Q3_K_S.gguf Q3_K_S 4.592 GB very small, high quality loss
GLM4-9B-Neon-v2-Q3_K_M.gguf Q3_K_M 4.975 GB very small, high quality loss
GLM4-9B-Neon-v2-Q3_K_L.gguf Q3_K_L 5.197 GB small, substantial quality loss
GLM4-9B-Neon-v2-Q4_0.gguf Q4_0 5.460 GB legacy; small, very high quality loss - prefer using Q3_K_M
GLM4-9B-Neon-v2-Q4_K_S.gguf Q4_K_S 5.758 GB small, greater quality loss
GLM4-9B-Neon-v2-Q4_K_M.gguf Q4_K_M 6.167 GB medium, balanced quality - recommended
GLM4-9B-Neon-v2-Q5_0.gguf Q5_0 6.557 GB legacy; medium, balanced quality - prefer using Q4_K_M
GLM4-9B-Neon-v2-Q5_K_S.gguf Q5_K_S 6.698 GB large, low quality loss - recommended
GLM4-9B-Neon-v2-Q5_K_M.gguf Q5_K_M 7.051 GB large, very low quality loss - recommended
GLM4-9B-Neon-v2-Q6_K.gguf Q6_K 8.267 GB very large, extremely low quality loss
GLM4-9B-Neon-v2-Q8_0.gguf Q8_0 10.000 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/allura-org_GLM4-9B-Neon-v2-GGUF --include "GLM4-9B-Neon-v2-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/allura-org_GLM4-9B-Neon-v2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
20
GGUF
Model size
9.4B params
Architecture
glm4
Hardware compatibility
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Model tree for tensorblock/allura-org_GLM4-9B-Neon-v2-GGUF

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Dataset used to train tensorblock/allura-org_GLM4-9B-Neon-v2-GGUF