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Delcos/Velara-11B-V2 - GGUF

This repo contains GGUF format model files for Delcos/Velara-11B-V2.

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

Prompt template

<|system|>
{system_prompt}</s>
<|user|>
{prompt}</s>
<|assistant|>

Model file specification

Filename Quant type File Size Description
Velara-11B-V2-Q2_K.gguf Q2_K 4.244 GB smallest, significant quality loss - not recommended for most purposes
Velara-11B-V2-Q3_K_S.gguf Q3_K_S 4.946 GB very small, high quality loss
Velara-11B-V2-Q3_K_M.gguf Q3_K_M 5.509 GB very small, high quality loss
Velara-11B-V2-Q3_K_L.gguf Q3_K_L 5.994 GB small, substantial quality loss
Velara-11B-V2-Q4_0.gguf Q4_0 6.441 GB legacy; small, very high quality loss - prefer using Q3_K_M
Velara-11B-V2-Q4_K_S.gguf Q4_K_S 6.487 GB small, greater quality loss
Velara-11B-V2-Q4_K_M.gguf Q4_K_M 6.846 GB medium, balanced quality - recommended
Velara-11B-V2-Q5_0.gguf Q5_0 7.847 GB legacy; medium, balanced quality - prefer using Q4_K_M
Velara-11B-V2-Q5_K_S.gguf Q5_K_S 7.847 GB large, low quality loss - recommended
Velara-11B-V2-Q5_K_M.gguf Q5_K_M 8.056 GB large, very low quality loss - recommended
Velara-11B-V2-Q6_K.gguf Q6_K 9.342 GB very large, extremely low quality loss
Velara-11B-V2-Q8_0.gguf Q8_0 12.099 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/Velara-11B-V2-GGUF --include "Velara-11B-V2-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/Velara-11B-V2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
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GGUF
Model size
11.4B params
Architecture
llama

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