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chujiezheng/Smaug-34B-v0.1-ExPO - GGUF

This repo contains GGUF format model files for chujiezheng/Smaug-34B-v0.1-ExPO.

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

Prompt template

[INST] <<SYS>>
{system_prompt}
<</SYS>>

{prompt} [/INST]

Model file specification

Filename Quant type File Size Description
Smaug-34B-v0.1-ExPO-Q2_K.gguf Q2_K 11.944 GB smallest, significant quality loss - not recommended for most purposes
Smaug-34B-v0.1-ExPO-Q3_K_S.gguf Q3_K_S 13.933 GB very small, high quality loss
Smaug-34B-v0.1-ExPO-Q3_K_M.gguf Q3_K_M 15.511 GB very small, high quality loss
Smaug-34B-v0.1-ExPO-Q3_K_L.gguf Q3_K_L 16.894 GB small, substantial quality loss
Smaug-34B-v0.1-ExPO-Q4_0.gguf Q4_0 18.130 GB legacy; small, very high quality loss - prefer using Q3_K_M
Smaug-34B-v0.1-ExPO-Q4_K_S.gguf Q4_K_S 18.253 GB small, greater quality loss
Smaug-34B-v0.1-ExPO-Q4_K_M.gguf Q4_K_M 19.240 GB medium, balanced quality - recommended
Smaug-34B-v0.1-ExPO-Q5_0.gguf Q5_0 22.080 GB legacy; medium, balanced quality - prefer using Q4_K_M
Smaug-34B-v0.1-ExPO-Q5_K_S.gguf Q5_K_S 22.080 GB large, low quality loss - recommended
Smaug-34B-v0.1-ExPO-Q5_K_M.gguf Q5_K_M 22.651 GB large, very low quality loss - recommended
Smaug-34B-v0.1-ExPO-Q6_K.gguf Q6_K 26.276 GB very large, extremely low quality loss
Smaug-34B-v0.1-ExPO-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/Smaug-34B-v0.1-ExPO-GGUF --include "Smaug-34B-v0.1-ExPO-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/Smaug-34B-v0.1-ExPO-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
35
GGUF
Model size
34.4B params
Architecture
llama

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Inference API
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