tensorblock/DataVortexS-10.7B-dpo-v1.1-GGUF

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Edentns/DataVortexS-10.7B-dpo-v1.1 - GGUF

This repo contains GGUF format model files for Edentns/DataVortexS-10.7B-dpo-v1.1.

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

Prompt template

### System:
{system_prompt}

### User:
{prompt}

### Assistant:

Model file specification

Filename	Quant type	File Size	Description
DataVortexS-10.7B-dpo-v1.1-Q2_K.gguf	Q2_K	3.793 GB	smallest, significant quality loss - not recommended for most purposes
DataVortexS-10.7B-dpo-v1.1-Q3_K_S.gguf	Q3_K_S	4.414 GB	very small, high quality loss
DataVortexS-10.7B-dpo-v1.1-Q3_K_M.gguf	Q3_K_M	4.909 GB	very small, high quality loss
DataVortexS-10.7B-dpo-v1.1-Q3_K_L.gguf	Q3_K_L	5.333 GB	small, substantial quality loss
DataVortexS-10.7B-dpo-v1.1-Q4_0.gguf	Q4_0	5.733 GB	legacy; small, very high quality loss - prefer using Q3_K_M
DataVortexS-10.7B-dpo-v1.1-Q4_K_S.gguf	Q4_K_S	5.776 GB	small, greater quality loss
DataVortexS-10.7B-dpo-v1.1-Q4_K_M.gguf	Q4_K_M	6.095 GB	medium, balanced quality - recommended
DataVortexS-10.7B-dpo-v1.1-Q5_0.gguf	Q5_0	6.974 GB	legacy; medium, balanced quality - prefer using Q4_K_M
DataVortexS-10.7B-dpo-v1.1-Q5_K_S.gguf	Q5_K_S	6.974 GB	large, low quality loss - recommended
DataVortexS-10.7B-dpo-v1.1-Q5_K_M.gguf	Q5_K_M	7.160 GB	large, very low quality loss - recommended
DataVortexS-10.7B-dpo-v1.1-Q6_K.gguf	Q6_K	8.292 GB	very large, extremely low quality loss
DataVortexS-10.7B-dpo-v1.1-Q8_0.gguf	Q8_0	10.740 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/DataVortexS-10.7B-dpo-v1.1-GGUF --include "DataVortexS-10.7B-dpo-v1.1-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/DataVortexS-10.7B-dpo-v1.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'