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01-ai/Yi-1.5-6B - GGUF

This repo contains GGUF format model files for 01-ai/Yi-1.5-6B.

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
Yi-1.5-6B-Q2_K.gguf Q2_K 2.177 GB smallest, significant quality loss - not recommended for most purposes
Yi-1.5-6B-Q3_K_S.gguf Q3_K_S 2.523 GB very small, high quality loss
Yi-1.5-6B-Q3_K_M.gguf Q3_K_M 2.787 GB very small, high quality loss
Yi-1.5-6B-Q3_K_L.gguf Q3_K_L 3.015 GB small, substantial quality loss
Yi-1.5-6B-Q4_0.gguf Q4_0 3.240 GB legacy; small, very high quality loss - prefer using Q3_K_M
Yi-1.5-6B-Q4_K_S.gguf Q4_K_S 3.262 GB small, greater quality loss
Yi-1.5-6B-Q4_K_M.gguf Q4_K_M 3.422 GB medium, balanced quality - recommended
Yi-1.5-6B-Q5_0.gguf Q5_0 3.915 GB legacy; medium, balanced quality - prefer using Q4_K_M
Yi-1.5-6B-Q5_K_S.gguf Q5_K_S 3.915 GB large, low quality loss - recommended
Yi-1.5-6B-Q5_K_M.gguf Q5_K_M 4.009 GB large, very low quality loss - recommended
Yi-1.5-6B-Q6_K.gguf Q6_K 4.633 GB very large, extremely low quality loss
Yi-1.5-6B-Q8_0.gguf Q8_0 6.000 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/Yi-1.5-6B-GGUF --include "Yi-1.5-6B-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/Yi-1.5-6B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
10
GGUF
Model size
6.06B params
Architecture
llama

2-bit

3-bit

4-bit

5-bit

6-bit

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Inference API
Unable to determine this model's library. Check the docs .

Model tree for tensorblock/Yi-1.5-6B-GGUF

Base model

01-ai/Yi-1.5-6B
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