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nztinversive/llama3.2-1b-Uncensored - GGUF

This repo contains GGUF format model files for nztinversive/llama3.2-1b-Uncensored.

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
llama3.2-1b-Uncensored-Q2_K.gguf Q2_K 0.581 GB smallest, significant quality loss - not recommended for most purposes
llama3.2-1b-Uncensored-Q3_K_S.gguf Q3_K_S 0.642 GB very small, high quality loss
llama3.2-1b-Uncensored-Q3_K_M.gguf Q3_K_M 0.691 GB very small, high quality loss
llama3.2-1b-Uncensored-Q3_K_L.gguf Q3_K_L 0.733 GB small, substantial quality loss
llama3.2-1b-Uncensored-Q4_0.gguf Q4_0 0.771 GB legacy; small, very high quality loss - prefer using Q3_K_M
llama3.2-1b-Uncensored-Q4_K_S.gguf Q4_K_S 0.776 GB small, greater quality loss
llama3.2-1b-Uncensored-Q4_K_M.gguf Q4_K_M 0.808 GB medium, balanced quality - recommended
llama3.2-1b-Uncensored-Q5_0.gguf Q5_0 0.893 GB legacy; medium, balanced quality - prefer using Q4_K_M
llama3.2-1b-Uncensored-Q5_K_S.gguf Q5_K_S 0.893 GB large, low quality loss - recommended
llama3.2-1b-Uncensored-Q5_K_M.gguf Q5_K_M 0.911 GB large, very low quality loss - recommended
llama3.2-1b-Uncensored-Q6_K.gguf Q6_K 1.022 GB very large, extremely low quality loss
llama3.2-1b-Uncensored-Q8_0.gguf Q8_0 1.321 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/llama3.2-1b-Uncensored-GGUF --include "llama3.2-1b-Uncensored-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/llama3.2-1b-Uncensored-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
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GGUF
Model size
1.24B params
Architecture
llama

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