TensorBlock

Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server

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
116
GGUF
Model size
11.4B params
Architecture
llama

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for tensorblock/Velara-11B-V2-GGUF

Quantized
(4)
this model