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microsoft/Phi-3-medium-4k-instruct - GGUF

This repo contains GGUF format model files for microsoft/Phi-3-medium-4k-instruct.

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

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Model file specification

Filename Quant type File Size Description
Phi-3-medium-4k-instruct-Q2_K.gguf Q2_K 4.790 GB smallest, significant quality loss - not recommended for most purposes
Phi-3-medium-4k-instruct-Q3_K_S.gguf Q3_K_S 5.648 GB very small, high quality loss
Phi-3-medium-4k-instruct-Q3_K_M.gguf Q3_K_M 6.448 GB very small, high quality loss
Phi-3-medium-4k-instruct-Q3_K_L.gguf Q3_K_L 6.976 GB small, substantial quality loss
Phi-3-medium-4k-instruct-Q4_0.gguf Q4_0 7.355 GB legacy; small, very high quality loss - prefer using Q3_K_M
Phi-3-medium-4k-instruct-Q4_K_S.gguf Q4_K_S 7.408 GB small, greater quality loss
Phi-3-medium-4k-instruct-Q4_K_M.gguf Q4_K_M 7.978 GB medium, balanced quality - recommended
Phi-3-medium-4k-instruct-Q5_0.gguf Q5_0 8.961 GB legacy; medium, balanced quality - prefer using Q4_K_M
Phi-3-medium-4k-instruct-Q5_K_S.gguf Q5_K_S 8.961 GB large, low quality loss - recommended
Phi-3-medium-4k-instruct-Q5_K_M.gguf Q5_K_M 9.382 GB large, very low quality loss - recommended
Phi-3-medium-4k-instruct-Q6_K.gguf Q6_K 10.667 GB very large, extremely low quality loss
Phi-3-medium-4k-instruct-Q8_0.gguf Q8_0 13.816 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/Phi-3-medium-4k-instruct-GGUF --include "Phi-3-medium-4k-instruct-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/Phi-3-medium-4k-instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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GGUF
Model size
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Architecture
phi3

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Inference Examples
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