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sid-du/comp8b-test-tokenizer - GGUF

This repo contains GGUF format model files for sid-du/comp8b-test-tokenizer.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

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
comp8b-test-tokenizer-Q2_K.gguf Q2_K 2.694 GB smallest, significant quality loss - not recommended for most purposes
comp8b-test-tokenizer-Q3_K_S.gguf Q3_K_S 3.098 GB very small, high quality loss
comp8b-test-tokenizer-Q3_K_M.gguf Q3_K_M 3.382 GB very small, high quality loss
comp8b-test-tokenizer-Q3_K_L.gguf Q3_K_L 3.633 GB small, substantial quality loss
comp8b-test-tokenizer-Q4_0.gguf Q4_0 3.921 GB legacy; small, very high quality loss - prefer using Q3_K_M
comp8b-test-tokenizer-Q4_K_S.gguf Q4_K_S 3.945 GB small, greater quality loss
comp8b-test-tokenizer-Q4_K_M.gguf Q4_K_M 4.132 GB medium, balanced quality - recommended
comp8b-test-tokenizer-Q5_0.gguf Q5_0 4.696 GB legacy; medium, balanced quality - prefer using Q4_K_M
comp8b-test-tokenizer-Q5_K_S.gguf Q5_K_S 4.696 GB large, low quality loss - recommended
comp8b-test-tokenizer-Q5_K_M.gguf Q5_K_M 4.804 GB large, very low quality loss - recommended
comp8b-test-tokenizer-Q6_K.gguf Q6_K 5.519 GB very large, extremely low quality loss
comp8b-test-tokenizer-Q8_0.gguf Q8_0 7.147 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/comp8b-test-tokenizer-GGUF --include "comp8b-test-tokenizer-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/comp8b-test-tokenizer-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
12
GGUF
Model size
6.72B params
Architecture
llama

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