nanollama-GGUF / README.md
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metadata
library_name: transformers
tags:
  - TensorBlock
  - GGUF
base_model: imdatta0/nanollama
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imdatta0/nanollama - GGUF

This repo contains GGUF format model files for imdatta0/nanollama.

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

Prompt template


Model file specification

Filename Quant type File Size Description
nanollama-Q2_K.gguf Q2_K 0.027 GB smallest, significant quality loss - not recommended for most purposes
nanollama-Q3_K_S.gguf Q3_K_S 0.031 GB very small, high quality loss
nanollama-Q3_K_M.gguf Q3_K_M 0.033 GB very small, high quality loss
nanollama-Q3_K_L.gguf Q3_K_L 0.035 GB small, substantial quality loss
nanollama-Q4_0.gguf Q4_0 0.039 GB legacy; small, very high quality loss - prefer using Q3_K_M
nanollama-Q4_K_S.gguf Q4_K_S 0.039 GB small, greater quality loss
nanollama-Q4_K_M.gguf Q4_K_M 0.040 GB medium, balanced quality - recommended
nanollama-Q5_0.gguf Q5_0 0.046 GB legacy; medium, balanced quality - prefer using Q4_K_M
nanollama-Q5_K_S.gguf Q5_K_S 0.046 GB large, low quality loss - recommended
nanollama-Q5_K_M.gguf Q5_K_M 0.046 GB large, very low quality loss - recommended
nanollama-Q6_K.gguf Q6_K 0.053 GB very large, extremely low quality loss
nanollama-Q8_0.gguf Q8_0 0.069 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/nanollama-GGUF --include "nanollama-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/nanollama-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'