README.md · tensorblock/Liph.42-GGUF at main

metadata

license: apache-2.0
tags:
  - phi
  - phi2
  - transformers
  - text-generation-inference
  - TensorBlock
  - GGUF
base_model: liminerity/Liph.42

Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server

liminerity/Liph.42 - GGUF

This repo contains GGUF format model files for liminerity/Liph.42.

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

Filename	Quant type	File Size	Description
Liph.42-Q2_K.gguf	Q2_K	1.110 GB	smallest, significant quality loss - not recommended for most purposes
Liph.42-Q3_K_S.gguf	Q3_K_S	1.251 GB	very small, high quality loss
Liph.42-Q3_K_M.gguf	Q3_K_M	1.426 GB	very small, high quality loss
Liph.42-Q3_K_L.gguf	Q3_K_L	1.575 GB	small, substantial quality loss
Liph.42-Q4_0.gguf	Q4_0	1.602 GB	legacy; small, very high quality loss - prefer using Q3_K_M
Liph.42-Q4_K_S.gguf	Q4_K_S	1.619 GB	small, greater quality loss
Liph.42-Q4_K_M.gguf	Q4_K_M	1.738 GB	medium, balanced quality - recommended
Liph.42-Q5_0.gguf	Q5_0	1.933 GB	legacy; medium, balanced quality - prefer using Q4_K_M
Liph.42-Q5_K_S.gguf	Q5_K_S	1.933 GB	large, low quality loss - recommended
Liph.42-Q5_K_M.gguf	Q5_K_M	2.003 GB	large, very low quality loss - recommended
Liph.42-Q6_K.gguf	Q6_K	2.285 GB	very large, extremely low quality loss
Liph.42-Q8_0.gguf	Q8_0	2.958 GB	very large, extremely low quality loss - not recommended

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/Liph.42-GGUF --include "Liph.42-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/Liph.42-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'