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artnoage/metastral_old - GGUF

This repo contains GGUF format model files for artnoage/metastral_old.

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

Prompt template

<s>[INST] {system_prompt}

{prompt}[/INST]

Model file specification

Filename Quant type File Size Description
metastral_old-Q2_K.gguf Q2_K 2.723 GB smallest, significant quality loss - not recommended for most purposes
metastral_old-Q3_K_S.gguf Q3_K_S 3.169 GB very small, high quality loss
metastral_old-Q3_K_M.gguf Q3_K_M 3.523 GB very small, high quality loss
metastral_old-Q3_K_L.gguf Q3_K_L 3.826 GB small, substantial quality loss
metastral_old-Q4_0.gguf Q4_0 4.113 GB legacy; small, very high quality loss - prefer using Q3_K_M
metastral_old-Q4_K_S.gguf Q4_K_S 4.145 GB small, greater quality loss
metastral_old-Q4_K_M.gguf Q4_K_M 4.373 GB medium, balanced quality - recommended
metastral_old-Q5_0.gguf Q5_0 5.002 GB legacy; medium, balanced quality - prefer using Q4_K_M
metastral_old-Q5_K_S.gguf Q5_K_S 5.002 GB large, low quality loss - recommended
metastral_old-Q5_K_M.gguf Q5_K_M 5.136 GB large, very low quality loss - recommended
metastral_old-Q6_K.gguf Q6_K 5.947 GB very large, extremely low quality loss
metastral_old-Q8_0.gguf Q8_0 7.703 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/metastral_old-GGUF --include "metastral_old-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/metastral_old-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
30
GGUF
Model size
7.25B params
Architecture
llama

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Inference Providers NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API: The model has no pipeline_tag.

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