tensorblock/Qwen2-7B-Instruct-GGUF

🤗 Hugging Face 来源apache-2.0激活 7B117 GBGGUF✓ 1 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/Qwen2-7B-Instruct-GGUF ./model-folder
需要做种者 →

unsloth/Qwen2-7B-Instruct - GGUF

This repo contains GGUF format model files for unsloth/Qwen2-7B-Instruct.

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

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## Prompt template
<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Model file specification

Filename Quant type File Size Description
Qwen2-7B-Instruct-Q2_K.gguf Q2_K 3.016 GB smallest, significant quality loss - not recommended for most purposes
Qwen2-7B-Instruct-Q3_K_S.gguf Q3_K_S 3.492 GB very small, high quality loss
Qwen2-7B-Instruct-Q3_K_M.gguf Q3_K_M 3.808 GB very small, high quality loss
Qwen2-7B-Instruct-Q3_K_L.gguf Q3_K_L 4.088 GB small, substantial quality loss
Qwen2-7B-Instruct-Q4_0.gguf Q4_0 4.431 GB legacy; small, very high quality loss - prefer using Q3_K_M
Qwen2-7B-Instruct-Q4_K_S.gguf Q4_K_S 4.458 GB small, greater quality loss
Qwen2-7B-Instruct-Q4_K_M.gguf Q4_K_M 4.683 GB medium, balanced quality - recommended
Qwen2-7B-Instruct-Q5_0.gguf Q5_0 5.315 GB legacy; medium, balanced quality - prefer using Q4_K_M
Qwen2-7B-Instruct-Q5_K_S.gguf Q5_K_S 5.315 GB large, low quality loss - recommended
Qwen2-7B-Instruct-Q5_K_M.gguf Q5_K_M 5.445 GB large, very low quality loss - recommended
Qwen2-7B-Instruct-Q6_K.gguf Q6_K 6.254 GB very large, extremely low quality loss
Qwen2-7B-Instruct-Q8_0.gguf Q8_0 8.099 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/Qwen2-7B-Instruct-GGUF --include "Qwen2-7B-Instruct-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/Qwen2-7B-Instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'