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claudiubarbu/orpo - GGUF

This repo contains GGUF format model files for claudiubarbu/orpo.

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
orpo-Q2_K.gguf Q2_K 0.081 GB smallest, significant quality loss - not recommended for most purposes
orpo-Q3_K_S.gguf Q3_K_S 0.090 GB very small, high quality loss
orpo-Q3_K_M.gguf Q3_K_M 0.098 GB very small, high quality loss
orpo-Q3_K_L.gguf Q3_K_L 0.102 GB small, substantial quality loss
orpo-Q4_0.gguf Q4_0 0.107 GB legacy; small, very high quality loss - prefer using Q3_K_M
orpo-Q4_K_S.gguf Q4_K_S 0.107 GB small, greater quality loss
orpo-Q4_K_M.gguf Q4_K_M 0.113 GB medium, balanced quality - recommended
orpo-Q5_0.gguf Q5_0 0.122 GB legacy; medium, balanced quality - prefer using Q4_K_M
orpo-Q5_K_S.gguf Q5_K_S 0.122 GB large, low quality loss - recommended
orpo-Q5_K_M.gguf Q5_K_M 0.127 GB large, very low quality loss - recommended
orpo-Q6_K.gguf Q6_K 0.138 GB very large, extremely low quality loss
orpo-Q8_0.gguf Q8_0 0.178 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/orpo-GGUF --include "orpo-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/orpo-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
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GGUF
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163M params
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gpt2

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Model tree for tensorblock/orpo-GGUF

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Dataset used to train tensorblock/orpo-GGUF