TensorBlock

Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server

CultriX/Qwen2.5-14B-Wernicke - GGUF

This repo contains GGUF format model files for CultriX/Qwen2.5-14B-Wernicke.

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

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
Qwen2.5-14B-Wernicke-Q2_K.gguf Q2_K 5.770 GB smallest, significant quality loss - not recommended for most purposes
Qwen2.5-14B-Wernicke-Q3_K_S.gguf Q3_K_S 6.660 GB very small, high quality loss
Qwen2.5-14B-Wernicke-Q3_K_M.gguf Q3_K_M 7.339 GB very small, high quality loss
Qwen2.5-14B-Wernicke-Q3_K_L.gguf Q3_K_L 7.925 GB small, substantial quality loss
Qwen2.5-14B-Wernicke-Q4_0.gguf Q4_0 8.518 GB legacy; small, very high quality loss - prefer using Q3_K_M
Qwen2.5-14B-Wernicke-Q4_K_S.gguf Q4_K_S 8.573 GB small, greater quality loss
Qwen2.5-14B-Wernicke-Q4_K_M.gguf Q4_K_M 8.988 GB medium, balanced quality - recommended
Qwen2.5-14B-Wernicke-Q5_0.gguf Q5_0 10.267 GB legacy; medium, balanced quality - prefer using Q4_K_M
Qwen2.5-14B-Wernicke-Q5_K_S.gguf Q5_K_S 10.267 GB large, low quality loss - recommended
Qwen2.5-14B-Wernicke-Q5_K_M.gguf Q5_K_M 10.509 GB large, very low quality loss - recommended
Qwen2.5-14B-Wernicke-Q6_K.gguf Q6_K 12.125 GB very large, extremely low quality loss
Qwen2.5-14B-Wernicke-Q8_0.gguf Q8_0 15.702 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/Qwen2.5-14B-Wernicke-GGUF --include "Qwen2.5-14B-Wernicke-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/Qwen2.5-14B-Wernicke-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
86
GGUF
Model size
14.8B params
Architecture
qwen2

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for tensorblock/Qwen2.5-14B-Wernicke-GGUF

Quantized
(4)
this model

Evaluation results