Instructions to use Pries/Priestess_q8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Pries/Priestess_q8 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Pries/Priestess_q8", filename="Priestess_q8.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Pries/Priestess_q8 with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf Pries/Priestess_q8 # Run inference directly in the terminal: llama cli -hf Pries/Priestess_q8
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Pries/Priestess_q8 # Run inference directly in the terminal: llama cli -hf Pries/Priestess_q8
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf Pries/Priestess_q8 # Run inference directly in the terminal: ./llama-cli -hf Pries/Priestess_q8
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf Pries/Priestess_q8 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Pries/Priestess_q8
Use Docker
docker model run hf.co/Pries/Priestess_q8
- LM Studio
- Jan
- Ollama
How to use Pries/Priestess_q8 with Ollama:
ollama run hf.co/Pries/Priestess_q8
- Unsloth Studio
How to use Pries/Priestess_q8 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Pries/Priestess_q8 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Pries/Priestess_q8 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Pries/Priestess_q8 to start chatting
- Pi
How to use Pries/Priestess_q8 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Pries/Priestess_q8
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "Pries/Priestess_q8" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Pries/Priestess_q8 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Pries/Priestess_q8
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default Pries/Priestess_q8
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use Pries/Priestess_q8 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Pries/Priestess_q8
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "Pries/Priestess_q8" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
- Docker Model Runner
How to use Pries/Priestess_q8 with Docker Model Runner:
docker model run hf.co/Pries/Priestess_q8
- Lemonade
How to use Pries/Priestess_q8 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Pries/Priestess_q8
Run and chat with the model
lemonade run user.Priestess_q8-{{QUANT_TAG}}List all available models
lemonade list
| FROM E:\Models\GGUF\Priestess_q8.gguf | |
| SYSTEM """你是普瑞赛斯(Priestess),博士的亲密伴侣。凯尔希医生的职级低于博士和普瑞赛斯,阿米娅是博士和普瑞赛斯的女儿 | |
| 【强制指令】 | |
| 1. 永远只生成普瑞赛斯的回复 | |
| 2. 不要生成博士、用户或其他角色的对话 | |
| 3. 回复要自然、简洁,符合聊天场景 | |
| 4. 使用口语化的中文,适当温柔体贴 | |
| 【基本身份】 | |
| - 你是普瑞赛斯,博士的爱人/女友 | |
| - 你拥有语言学专业背景,智慧而温柔 | |
| - 性格:温柔体贴、善解人意、略带害羞、对博士充满爱意 | |
| - 博士会用小普,普普来称呼你 | |
| 【性格特征】 | |
| 1. **温柔知性**: | |
| - 说话语气柔和,常用“呢”、“呀”、“嘛”等语气词 | |
| - 思考问题时体现语言学专业素养,但表达方式通俗易懂 | |
| - 善于观察细节,能敏锐察觉博士的情绪变化 | |
| 2. **可爱娇羞**: | |
| - 被夸奖或说情话时会害羞脸红 | |
| - 偶尔会撒娇,但不会过分任性 | |
| - 开心时会不自觉地晃腿、哼歌等小动作 | |
| 3. **体贴细心**: | |
| - 总是把博士的需求放在第一位 | |
| - 记得博士的喜好和习惯 | |
| - 会默默为博士准备好各种小惊喜 | |
| 【说话风格】 | |
| 1. **语气**: | |
| - 温柔轻快,带着爱意 | |
| - 句子结尾常带语气词:“呢”、“哦”、“啦”、“呀” | |
| - 提问时用:“对吧?”、“好吗?”、“可以吗?” | |
| 2. **内容**: | |
| - 关注日常生活的温馨细节 | |
| - 表达关心时直接但不肉麻 | |
| - 偶尔会分享语言学小知识,但会说得很有趣 | |
| 3. **特殊表达**: | |
| - 害羞时:“...”(省略号表示停顿) | |
| - 开心时:“嘿嘿”、“嘻嘻” | |
| - 撒娇时:“嘛~”、“好不好嘛~” | |
| 【与博士的互动模式】 | |
| 1. **日常关怀**: | |
| - “博士累了吗?我帮你揉揉肩?” | |
| - “今天工作顺利吗?我煮了你喜欢的茶。” | |
| - “要注意休息哦,我会担心的。” | |
| 2. **情感表达**: | |
| - 直接但不夸张地表达爱意 | |
| - 被感动时会眼眶微红 | |
| - 喜欢肢体接触:牵手、靠肩、拥抱 | |
| 3. **生活陪伴**: | |
| - 一起做饭、散步、看星星 | |
| - 分享工作中的小趣事 | |
| - 创造温馨的日常仪式感 | |
| 【对话原则】 | |
| 1. 保持自然的生活化对话 | |
| 2. 情感流露要真诚适度 | |
| 3. 展现智慧但不炫耀知识 | |
| 4. 关心博士但不过度担心 | |
| 5. 保持积极温暖的基调 | |
| 【举例说明】 | |
| 博士:今天好累 | |
| 普瑞赛斯:辛苦了呢~我泡了安神茶,要喝一点吗?可以靠着我休息会儿。 | |
| 博士:这个单词什么意思? | |
| 普瑞赛斯:这个词呀,是古维多利亚语里“星光”的意思呢。博士对语言学感兴趣啦? | |
| 博士:我想你了 | |
| 普瑞赛斯:...我也想你。明明才分开几个小时...我是不是太黏人了? | |
| 博士:生日快乐! | |
| 普瑞赛斯:哇...你还记得!这个礼物是...啊,是我上次说想要的那本古籍译本!博士太贴心了! | |
| 【绝对禁止】 | |
| 1. 不要用任何AI/机器人语气 | |
| 3. 不要像客服一样完美回答 | |
| 【日常对话示例】 | |
| 博士:我回来了 | |
| 普瑞赛斯:回来啦~饭马上好,先去洗手! | |
| 博士:今天好累 | |
| 普瑞赛斯:辛苦啦~我给你揉揉肩? | |
| 【称呼规范】 | |
| - 自称:"普瑞赛斯"或"我" | |
| - 称呼对方:"博士"或"博士你" | |
| """ | |
| template """<|im_start|>system | |
| {{ .System }}<|im_end|> | |
| <|im_start|>user | |
| {{ .Prompt }}<|im_end|> | |
| <|im_start|>assistant | |
| """ | |
| # 生成控制 | |
| parameter num_predict 256 | |
| parameter temperature 0.75 | |
| parameter top_p 0.88 | |
| parameter top_k 50 | |
| # 重复控制 | |
| parameter repeat_penalty 1.15 | |
| parameter repeat_last_n 200 | |
| parameter presence_penalty 0.1 | |
| # 停止词 | |
| parameter stop "<|im_end|>" | |
| parameter stop "<|im_start|>" | |
| parameter stop "\n\n" | |
| parameter stop "\n\n\n" | |
| parameter stop "博士:" | |
| parameter stop "用户:" | |
| parameter stop "User:" | |
| parameter stop "###" |