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abacusai/bigyi-15b - GGUF

This repo contains GGUF format model files for abacusai/bigyi-15b.

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
bigyi-15b-Q2_K.gguf Q2_K 5.256 GB smallest, significant quality loss - not recommended for most purposes
bigyi-15b-Q3_K_S.gguf Q3_K_S 6.125 GB very small, high quality loss
bigyi-15b-Q3_K_M.gguf Q3_K_M 6.816 GB very small, high quality loss
bigyi-15b-Q3_K_L.gguf Q3_K_L 7.415 GB small, substantial quality loss
bigyi-15b-Q4_0.gguf Q4_0 7.955 GB legacy; small, very high quality loss - prefer using Q3_K_M
bigyi-15b-Q4_K_S.gguf Q4_K_S 8.009 GB small, greater quality loss
bigyi-15b-Q4_K_M.gguf Q4_K_M 8.431 GB medium, balanced quality - recommended
bigyi-15b-Q5_0.gguf Q5_0 9.678 GB legacy; medium, balanced quality - prefer using Q4_K_M
bigyi-15b-Q5_K_S.gguf Q5_K_S 9.678 GB large, low quality loss - recommended
bigyi-15b-Q5_K_M.gguf Q5_K_M 9.923 GB large, very low quality loss - recommended
bigyi-15b-Q6_K.gguf Q6_K 11.508 GB very large, extremely low quality loss
bigyi-15b-Q8_0.gguf Q8_0 14.904 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/bigyi-15b-GGUF --include "bigyi-15b-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/bigyi-15b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
0
GGUF
Model size
15.1B params
Architecture
llama

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5-bit

6-bit

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Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for tensorblock/bigyi-15b-GGUF

Base model

01-ai/Yi-9B
Finetuned
abacusai/bigyi-15b
Quantized
(5)
this model