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kenhktsui/nano-phi-115M-v0.1 - GGUF

This repo contains GGUF format model files for kenhktsui/nano-phi-115M-v0.1.

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

Prompt template


Model file specification

Filename Quant type File Size Description
nano-phi-115M-v0.1-Q2_K.gguf Q2_K 0.061 GB smallest, significant quality loss - not recommended for most purposes
nano-phi-115M-v0.1-Q3_K_S.gguf Q3_K_S 0.067 GB very small, high quality loss
nano-phi-115M-v0.1-Q3_K_M.gguf Q3_K_M 0.069 GB very small, high quality loss
nano-phi-115M-v0.1-Q3_K_L.gguf Q3_K_L 0.072 GB small, substantial quality loss
nano-phi-115M-v0.1-Q4_0.gguf Q4_0 0.077 GB legacy; small, very high quality loss - prefer using Q3_K_M
nano-phi-115M-v0.1-Q4_K_S.gguf Q4_K_S 0.077 GB small, greater quality loss
nano-phi-115M-v0.1-Q4_K_M.gguf Q4_K_M 0.078 GB medium, balanced quality - recommended
nano-phi-115M-v0.1-Q5_0.gguf Q5_0 0.086 GB legacy; medium, balanced quality - prefer using Q4_K_M
nano-phi-115M-v0.1-Q5_K_S.gguf Q5_K_S 0.086 GB large, low quality loss - recommended
nano-phi-115M-v0.1-Q5_K_M.gguf Q5_K_M 0.087 GB large, very low quality loss - recommended
nano-phi-115M-v0.1-Q6_K.gguf Q6_K 0.096 GB very large, extremely low quality loss
nano-phi-115M-v0.1-Q8_0.gguf Q8_0 0.124 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/nano-phi-115M-v0.1-GGUF --include "nano-phi-115M-v0.1-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/nano-phi-115M-v0.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
122
GGUF
Model size
115M params
Architecture
phi2

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Inference Examples
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Datasets used to train tensorblock/nano-phi-115M-v0.1-GGUF

Evaluation results