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Deacon-34B-GGUF

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metadata
pipeline_tag: text-generation
datasets:
  - totally-not-an-llm/EverythingLM-data-V3
license: apache-2.0
tags:
  - TensorBlock
  - GGUF
base_model: KnutJaegersberg/Deacon-34B
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KnutJaegersberg/Deacon-34B - GGUF

This repo contains GGUF format model files for KnutJaegersberg/Deacon-34B.

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
Deacon-34B-Q2_K.gguf Q2_K 11.944 GB smallest, significant quality loss - not recommended for most purposes
Deacon-34B-Q3_K_S.gguf Q3_K_S 13.933 GB very small, high quality loss
Deacon-34B-Q3_K_M.gguf Q3_K_M 15.511 GB very small, high quality loss
Deacon-34B-Q3_K_L.gguf Q3_K_L 16.894 GB small, substantial quality loss
Deacon-34B-Q4_0.gguf Q4_0 18.130 GB legacy; small, very high quality loss - prefer using Q3_K_M
Deacon-34B-Q4_K_S.gguf Q4_K_S 18.253 GB small, greater quality loss
Deacon-34B-Q4_K_M.gguf Q4_K_M 19.240 GB medium, balanced quality - recommended
Deacon-34B-Q5_0.gguf Q5_0 22.080 GB legacy; medium, balanced quality - prefer using Q4_K_M
Deacon-34B-Q5_K_S.gguf Q5_K_S 22.080 GB large, low quality loss - recommended
Deacon-34B-Q5_K_M.gguf Q5_K_M 22.651 GB large, very low quality loss - recommended
Deacon-34B-Q6_K.gguf Q6_K 26.276 GB very large, extremely low quality loss
Deacon-34B-Q8_0.gguf Q8_0 34.033 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/Deacon-34B-GGUF --include "Deacon-34B-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/Deacon-34B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'