tensorblock/llm4decompile-9b-v2-GGUF

🤗 Hugging Face 来源mit激活 9B67 GBGGUF✓ 2 个校验和今天更新
一条命令提交

在你的模型文件夹旁边运行它。它会制作种子、将文件与 Hugging Face 比对,然后提交。你只需开始做种,并粘贴你账户中的密钥。它只读取你的文件,绝不修改。如果愿意,可以先阅读脚本。

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo tensorblock/llm4decompile-9b-v2-GGUF ./model-folder
需要做种者 →

LLM4Binary/llm4decompile-9b-v2 - GGUF

This repo contains GGUF format model files for LLM4Binary/llm4decompile-9b-v2.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4658.

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## Prompt template
{system_prompt}{prompt}

Model file specification

Filename Quant type File Size Description
llm4decompile-9b-v2-Q2_K.gguf Q2_K 3.354 GB smallest, significant quality loss - not recommended for most purposes
llm4decompile-9b-v2-Q3_K_S.gguf Q3_K_S 3.899 GB very small, high quality loss
llm4decompile-9b-v2-Q3_K_M.gguf Q3_K_M 4.324 GB very small, high quality loss
llm4decompile-9b-v2-Q3_K_L.gguf Q3_K_L 4.691 GB small, substantial quality loss
llm4decompile-9b-v2-Q4_0.gguf Q4_0 5.037 GB legacy; small, very high quality loss - prefer using Q3_K_M
llm4decompile-9b-v2-Q4_K_S.gguf Q4_K_S 5.072 GB small, greater quality loss
llm4decompile-9b-v2-Q4_K_M.gguf Q4_K_M 5.329 GB medium, balanced quality - recommended
llm4decompile-9b-v2-Q5_0.gguf Q5_0 6.108 GB legacy; medium, balanced quality - prefer using Q4_K_M
llm4decompile-9b-v2-Q5_K_S.gguf Q5_K_S 6.108 GB large, low quality loss - recommended
llm4decompile-9b-v2-Q5_K_M.gguf Q5_K_M 6.258 GB large, very low quality loss - recommended
llm4decompile-9b-v2-Q6_K.gguf Q6_K 7.246 GB very large, extremely low quality loss
llm4decompile-9b-v2-Q8_0.gguf Q8_0 9.384 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-9b-v2-GGUF --include "llm4decompile-9b-v2-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-9b-v2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'