Quantization Format (GGUF)

We use llama.cpp release b5572 for quantization. Original model: https://huggingface.co/pot99rta/GoldFusionReiV3-12B

Download a file (not the whole branch) from below:

Filename	Quant type	File Size	Split
goldfusionreiv3-12b-q5_k_m.gguf	Q5_K_M	8.13 GB	False

Original Model Card

merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the TIES merge method using Delta-Vector/Rei-V3-KTO-12B as a base.

Models Merged

The following models were included in the merge:

pot99rta/GoldFusion-12B

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: Delta-Vector/Rei-V3-KTO-12B
    #no parameters necessary for base model
  - model: Delta-Vector/Rei-V3-KTO-12B
    parameters:
      density: 0.5
      weight: 0.5
  - model: pot99rta/GoldFusion-12B
    parameters:
      density: 0.5
      weight: 0.5

merge_method: ties
base_model: Delta-Vector/Rei-V3-KTO-12B
parameters:
  normalize: false
  int8_mask: true
dtype: float16

Downloading using huggingface-cli

Click to view download instructions

First, make sure you have hugginface-cli installed:

pip install -U "huggingface_hub[cli]"

Then, you can target the specific file you want:

huggingface-cli download https://huggingface.co/perfectlygray/GoldFusionReiV3-12B-GGUF --include "goldfusionreiv3-12b-q5_k_m.gguf" --local-dir ./

If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run:

huggingface-cli download https://huggingface.co/perfectlygray/GoldFusionReiV3-12B-GGUF --include "goldfusionreiv3-12b-q5_k_m.gguf/*" --local-dir ./

You can either specify a new local-dir (e.g. deepseek-ai_DeepSeek-V3-0324-Q8_0) or it will be in default hugging face cache

perfectlygray
/

GoldFusionReiV3-12B-GGUF