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silma-ai/SILMA-9B-Instruct-v1.0 - GGUF

This repo contains GGUF format model files for silma-ai/SILMA-9B-Instruct-v1.0.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Prompt template

<bos>{system_prompt}<start_of_turn>user
{prompt}<end_of_turn>
<start_of_turn>model

Model file specification

Filename Quant type File Size Description
SILMA-9B-Instruct-v1.0-Q2_K.gguf Q2_K 3.544 GB smallest, significant quality loss - not recommended for most purposes
SILMA-9B-Instruct-v1.0-Q3_K_S.gguf Q3_K_S 4.040 GB very small, high quality loss
SILMA-9B-Instruct-v1.0-Q3_K_M.gguf Q3_K_M 4.435 GB very small, high quality loss
SILMA-9B-Instruct-v1.0-Q3_K_L.gguf Q3_K_L 4.780 GB small, substantial quality loss
SILMA-9B-Instruct-v1.0-Q4_0.gguf Q4_0 5.069 GB legacy; small, very high quality loss - prefer using Q3_K_M
SILMA-9B-Instruct-v1.0-Q4_K_S.gguf Q4_K_S 5.103 GB small, greater quality loss
SILMA-9B-Instruct-v1.0-Q4_K_M.gguf Q4_K_M 5.365 GB medium, balanced quality - recommended
SILMA-9B-Instruct-v1.0-Q5_0.gguf Q5_0 6.038 GB legacy; medium, balanced quality - prefer using Q4_K_M
SILMA-9B-Instruct-v1.0-Q5_K_S.gguf Q5_K_S 6.038 GB large, low quality loss - recommended
SILMA-9B-Instruct-v1.0-Q5_K_M.gguf Q5_K_M 6.191 GB large, very low quality loss - recommended
SILMA-9B-Instruct-v1.0-Q6_K.gguf Q6_K 7.068 GB very large, extremely low quality loss
SILMA-9B-Instruct-v1.0-Q8_0.gguf Q8_0 9.152 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/SILMA-9B-Instruct-v1.0-GGUF --include "SILMA-9B-Instruct-v1.0-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/SILMA-9B-Instruct-v1.0-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
14,162
GGUF
Model size
9.24B params
Architecture
gemma2

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Inference Examples
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Evaluation results