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nicholasKluge/TeenyTinyLlama-160m - GGUF

This repo contains GGUF format model files for nicholasKluge/TeenyTinyLlama-160m.

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
TeenyTinyLlama-160m-Q2_K.gguf Q2_K 0.071 GB smallest, significant quality loss - not recommended for most purposes
TeenyTinyLlama-160m-Q3_K_S.gguf Q3_K_S 0.080 GB very small, high quality loss
TeenyTinyLlama-160m-Q3_K_M.gguf Q3_K_M 0.086 GB very small, high quality loss
TeenyTinyLlama-160m-Q3_K_L.gguf Q3_K_L 0.091 GB small, substantial quality loss
TeenyTinyLlama-160m-Q4_0.gguf Q4_0 0.099 GB legacy; small, very high quality loss - prefer using Q3_K_M
TeenyTinyLlama-160m-Q4_K_S.gguf Q4_K_S 0.099 GB small, greater quality loss
TeenyTinyLlama-160m-Q4_K_M.gguf Q4_K_M 0.103 GB medium, balanced quality - recommended
TeenyTinyLlama-160m-Q5_0.gguf Q5_0 0.116 GB legacy; medium, balanced quality - prefer using Q4_K_M
TeenyTinyLlama-160m-Q5_K_S.gguf Q5_K_S 0.116 GB large, low quality loss - recommended
TeenyTinyLlama-160m-Q5_K_M.gguf Q5_K_M 0.118 GB large, very low quality loss - recommended
TeenyTinyLlama-160m-Q6_K.gguf Q6_K 0.134 GB very large, extremely low quality loss
TeenyTinyLlama-160m-Q8_0.gguf Q8_0 0.173 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/TeenyTinyLlama-160m-GGUF --include "TeenyTinyLlama-160m-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/TeenyTinyLlama-160m-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
101
GGUF
Model size
162M params
Architecture
llama

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Inference Examples
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Dataset used to train tensorblock/TeenyTinyLlama-160m-GGUF

Evaluation results