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LLM4Binary/llm4decompile-1.3b-v1.5 - GGUF

This repo contains GGUF format model files for LLM4Binary/llm4decompile-1.3b-v1.5.

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
llm4decompile-1.3b-v1.5-Q2_K.gguf Q2_K 0.560 GB smallest, significant quality loss - not recommended for most purposes
llm4decompile-1.3b-v1.5-Q3_K_S.gguf Q3_K_S 0.642 GB very small, high quality loss
llm4decompile-1.3b-v1.5-Q3_K_M.gguf Q3_K_M 0.704 GB very small, high quality loss
llm4decompile-1.3b-v1.5-Q3_K_L.gguf Q3_K_L 0.744 GB small, substantial quality loss
llm4decompile-1.3b-v1.5-Q4_0.gguf Q4_0 0.776 GB legacy; small, very high quality loss - prefer using Q3_K_M
llm4decompile-1.3b-v1.5-Q4_K_S.gguf Q4_K_S 0.814 GB small, greater quality loss
llm4decompile-1.3b-v1.5-Q4_K_M.gguf Q4_K_M 0.873 GB medium, balanced quality - recommended
llm4decompile-1.3b-v1.5-Q5_0.gguf Q5_0 0.936 GB legacy; medium, balanced quality - prefer using Q4_K_M
llm4decompile-1.3b-v1.5-Q5_K_S.gguf Q5_K_S 0.953 GB large, low quality loss - recommended
llm4decompile-1.3b-v1.5-Q5_K_M.gguf Q5_K_M 1.002 GB large, very low quality loss - recommended
llm4decompile-1.3b-v1.5-Q6_K.gguf Q6_K 1.172 GB very large, extremely low quality loss
llm4decompile-1.3b-v1.5-Q8_0.gguf Q8_0 1.432 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/llm4decompile-1.3b-v1.5-GGUF --include "llm4decompile-1.3b-v1.5-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/llm4decompile-1.3b-v1.5-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
30
GGUF
Model size
1.35B params
Architecture
llama

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Inference API
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