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vihangd/shearedplats-2.7b-v1 - GGUF

This repo contains GGUF format model files for vihangd/shearedplats-2.7b-v1.

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
shearedplats-2.7b-v1-Q2_K.gguf Q2_K 1.028 GB smallest, significant quality loss - not recommended for most purposes
shearedplats-2.7b-v1-Q3_K_S.gguf Q3_K_S 1.194 GB very small, high quality loss
shearedplats-2.7b-v1-Q3_K_M.gguf Q3_K_M 1.331 GB very small, high quality loss
shearedplats-2.7b-v1-Q3_K_L.gguf Q3_K_L 1.448 GB small, substantial quality loss
shearedplats-2.7b-v1-Q4_0.gguf Q4_0 1.542 GB legacy; small, very high quality loss - prefer using Q3_K_M
shearedplats-2.7b-v1-Q4_K_S.gguf Q4_K_S 1.554 GB small, greater quality loss
shearedplats-2.7b-v1-Q4_K_M.gguf Q4_K_M 1.642 GB medium, balanced quality - recommended
shearedplats-2.7b-v1-Q5_0.gguf Q5_0 1.869 GB legacy; medium, balanced quality - prefer using Q4_K_M
shearedplats-2.7b-v1-Q5_K_S.gguf Q5_K_S 1.869 GB large, low quality loss - recommended
shearedplats-2.7b-v1-Q5_K_M.gguf Q5_K_M 1.921 GB large, very low quality loss - recommended
shearedplats-2.7b-v1-Q6_K.gguf Q6_K 2.217 GB very large, extremely low quality loss
shearedplats-2.7b-v1-Q8_0.gguf Q8_0 2.872 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/shearedplats-2.7b-v1-GGUF --include "shearedplats-2.7b-v1-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/shearedplats-2.7b-v1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
169
GGUF
Model size
2.7B params
Architecture
llama

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Inference API
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