Sorry about that bad link. Here it is.

Install ollama

```sh
pacman -S ollama
```

Download any uncensored llm

From ollama's library

Serve, Pull, and Run

1. In terminal A execute

   ollama serve
   

2. In terminal B execute

   ollama pull wizard-vicuna-uncensored:7B
   ollama run wizard-vicuna-uncensored:7B
   

From huggingface

download and any gguf model you want with uncensored in the name. I like ggufs from TheBloke

• Example using SOLAR-10.7B-Instruct-v1.0-uncensored-GGUF
  • Click on Files and Versons and download solar-10.7b-instruct-v1.0-uncensored.Q5_K_S.gguf
  • change directory to where the downloaded gguf is and write a modelfile with just a FROM line

    echo "FROM ~/Documents/ollama/models/solar-10.7b-instruct-v1.0-uncensored.Q5_K_S.gguf" >| ~/Documents/ollama/modelfiles/solar-10.7b-instruct-v1.0-uncensored.Q5_K_S.gguf.modelfile
    

  • Serve, Create, and Run
    1. In terminal A execute

       ollama serve
       

    2. In terminal B execute

       ollama create solar-10:7b -f ~/Documents/ollama/modelfiles/solar-10.7b-instruct-v1.0-uncensored.Q5_K_S.gguf.modelfile
       ollama run solar-10:7b
       

Create a GGUF file from a non gguf llm for ollama

setup python env

Install pyenv and then follow instructions to update .bashrc

curl https://pyenv.run/ | bash

Update pyenv and install a version of python you need

source "${HOME}"/.bashrc
pyenv update
pyenv install 3.9

Create a virtual environment

pyenv virtualenv 3.9 ggufc

Use the virtual environment and download the pre-reqs

pyenv activate ggufc
pip install --upgrade pip
pip install huggingface_hub
mkdir -p ~/Documents/ollama/python
cd ~/Documents/ollama/python
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
pip install -r requirements.txt

Download the model from huggingface.

For this example, Im going to pull llama3.2_1b_2025_uncensored Note that this llm is 1B so can be ran on a low spec device.

mkdir -p ~/Documents/ollama/python
mkdir -p ~/Documents/ollama/models
model_repo_slug='carsenk'
model_repo_name='llama3.2_1b_2025_uncensored'
model_id="$model_repo_slug/$model_repo_name"
cat << EOF >| ~/Documents/ollama/python/fetch.py
from huggingface_hub import snapshot_download

model_id="$model_id"
snapshot_download(repo_id=model_id, local_dir="$model_id",
                  local_dir_use_symlinks=False, revision="main")
EOF

cd ~/Documents/ollama/models
python ~/Documents/ollama/python/fetch.py

Transpose HF to GGUF

python ~/Documents/ollama/python/llama.cpp/convert.py "$model_id" \
  --outfile "$model_repo_name".gguf \
  --outtype q8_0

Serve, Organize, Create, and Run

1. In terminal A execute

   ollama serve
   

2. Open a new terminal while ollama is being served.

   mkdir -p ~/Documents/ollama/modelfiles
   echo "FROM ~/Documents/ollama/models/llama3.2_1b_2025_uncensored.gguf" >| ~/Documents/ollama/modelfiles/llama3.2_1b_2025_uncensored.modelfile
   ollama create llama3.2:1b -f ~/Documents/ollama/modelfiles/llama3.2_1b_2025_uncensored.modelfile
   ollama run llama3.2:1b