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HuggingFaceFW/ablation-model-fineweb-edu - GGUF

This repo contains GGUF format model files for HuggingFaceFW/ablation-model-fineweb-edu.

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
ablation-model-fineweb-edu-Q2_K.gguf Q2_K 0.630 GB smallest, significant quality loss - not recommended for most purposes
ablation-model-fineweb-edu-Q3_K_S.gguf Q3_K_S 0.725 GB very small, high quality loss
ablation-model-fineweb-edu-Q3_K_M.gguf Q3_K_M 0.803 GB very small, high quality loss
ablation-model-fineweb-edu-Q3_K_L.gguf Q3_K_L 0.870 GB small, substantial quality loss
ablation-model-fineweb-edu-Q4_0.gguf Q4_0 0.924 GB legacy; small, very high quality loss - prefer using Q3_K_M
ablation-model-fineweb-edu-Q4_K_S.gguf Q4_K_S 0.932 GB small, greater quality loss
ablation-model-fineweb-edu-Q4_K_M.gguf Q4_K_M 0.985 GB medium, balanced quality - recommended
ablation-model-fineweb-edu-Q5_0.gguf Q5_0 1.112 GB legacy; medium, balanced quality - prefer using Q4_K_M
ablation-model-fineweb-edu-Q5_K_S.gguf Q5_K_S 1.112 GB large, low quality loss - recommended
ablation-model-fineweb-edu-Q5_K_M.gguf Q5_K_M 1.143 GB large, very low quality loss - recommended
ablation-model-fineweb-edu-Q6_K.gguf Q6_K 1.311 GB very large, extremely low quality loss
ablation-model-fineweb-edu-Q8_0.gguf Q8_0 1.698 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/ablation-model-fineweb-edu-GGUF --include "ablation-model-fineweb-edu-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/ablation-model-fineweb-edu-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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llama

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