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arcee-ai/arcee-lite - GGUF

This repo contains GGUF format model files for arcee-ai/arcee-lite.

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
arcee-lite-Q2_K.gguf Q2_K 0.753 GB smallest, significant quality loss - not recommended for most purposes
arcee-lite-Q3_K_S.gguf Q3_K_S 0.861 GB very small, high quality loss
arcee-lite-Q3_K_M.gguf Q3_K_M 0.924 GB very small, high quality loss
arcee-lite-Q3_K_L.gguf Q3_K_L 0.980 GB small, substantial quality loss
arcee-lite-Q4_0.gguf Q4_0 1.066 GB legacy; small, very high quality loss - prefer using Q3_K_M
arcee-lite-Q4_K_S.gguf Q4_K_S 1.072 GB small, greater quality loss
arcee-lite-Q4_K_M.gguf Q4_K_M 1.117 GB medium, balanced quality - recommended
arcee-lite-Q5_0.gguf Q5_0 1.259 GB legacy; medium, balanced quality - prefer using Q4_K_M
arcee-lite-Q5_K_S.gguf Q5_K_S 1.259 GB large, low quality loss - recommended
arcee-lite-Q5_K_M.gguf Q5_K_M 1.285 GB large, very low quality loss - recommended
arcee-lite-Q6_K.gguf Q6_K 1.464 GB very large, extremely low quality loss
arcee-lite-Q8_0.gguf Q8_0 1.895 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/arcee-lite-GGUF --include "arcee-lite-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/arcee-lite-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
1.78B params
Architecture
qwen2

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Inference API
Unable to determine this model's library. Check the docs .

Model tree for tensorblock/arcee-lite-GGUF

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