Instructions to use amandoti/cluemaster-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use amandoti/cluemaster-1.0 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 amandoti/cluemaster-1.0:Q4_K_M # Run inference directly in the terminal: llama cli -hf amandoti/cluemaster-1.0:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf amandoti/cluemaster-1.0:Q4_K_M # Run inference directly in the terminal: llama cli -hf amandoti/cluemaster-1.0:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf amandoti/cluemaster-1.0:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf amandoti/cluemaster-1.0:Q4_K_M
Use Docker
docker model run hf.co/amandoti/cluemaster-1.0:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use amandoti/cluemaster-1.0 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "amandoti/cluemaster-1.0" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "amandoti/cluemaster-1.0", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/amandoti/cluemaster-1.0:Q4_K_M
- Ollama
How to use amandoti/cluemaster-1.0 with Ollama:
ollama run hf.co/amandoti/cluemaster-1.0:Q4_K_M
- Unsloth Desktop
- Pi
How to use amandoti/cluemaster-1.0 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf amandoti/cluemaster-1.0:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "amandoti/cluemaster-1.0:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use amandoti/cluemaster-1.0 with Docker Model Runner:
docker model run hf.co/amandoti/cluemaster-1.0:Q4_K_M
- Lemonade
How to use amandoti/cluemaster-1.0 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull amandoti/cluemaster-1.0:Q4_K_M
Run and chat with the model
lemonade run user.cluemaster-1.0-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use amandoti/cluemaster-1.0 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf amandoti/cluemaster-1.0:Q4_K_M
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 amandoti/cluemaster-1.0:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use amandoti/cluemaster-1.0 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf amandoti/cluemaster-1.0:Q4_K_M
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 "amandoti/cluemaster-1.0:Q4_K_M" \ --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"
Cluemaster 1.0
A 3B Codenames spymaster. It reads a board and the clues so far, and answers with a short brainstorm, then a clue, a number and the target words.
- Base model: Ministral 3 3B Instruct, LoRA fine-tuned (rank 16, alpha 32, all attention and MLP layers).
- Format: GGUF, Q4_K_M, 2.1 GB.
- Runs in: Ollama, llama.cpp, LM Studio. About 3 GB of free memory; a 6 GB graphics card runs it fully on the GPU.
Results
Cluebench v1.0. Every clue was rated good, ok or bad in a blind rating, on held-out boards sealed before training. Every model got the same board and format, one answer at temperature 0. Cluemaster was benchmarked as the Q4_K_M file. The leader of each column is in bold.
Overall
| Model | Cluebench | Rated good | Acceptable | Legal first try | Illegal | Invalid | Seconds per board | Tokens per answer |
|---|---|---|---|---|---|---|---|---|
| Cluemaster 1.0 | 60% | 44% | 68% | 96% | 4% | 0% | 2.5 s | 93 |
| Phi-4 Mini 3.8B | 20% | 17% | 34% | 63% | 37% | 1% | 1.4 s | 33 |
| Granite 4.1 3B | 20% | 12% | 33% | 76% | 24% | 2% | 0.6 s | 19 |
| Ministral 3 3B | 5% | 5% | 19% | 61% | 39% | 6% | 2.8 s | 53 |
| Qwen 3.5 4B | 3% | 13% | 17% | 25% | 75% | 0% | 1.9 s | 29 |
Acceptable is legal and rated good or ok. Illegal is a clue that breaks a rule. Invalid is a legal clue aimed at a neutral or opponent word.
Fresh boards
| Model | Score | Good | Acceptable | Illegal |
|---|---|---|---|---|
| Cluemaster 1.0 | 72 | 45% | 85% | 5% |
| Phi-4 Mini 3.8B | 33 | 32% | 47% | 37% |
| Granite 4.1 3B | 22 | 12% | 37% | 25% |
| Ministral 3 3B | 7 | 8% | 23% | 45% |
| Qwen 3.5 4B | 0 | 2% | 5% | 90% |
Midgame (4 or more of your words left)
| Model | Score | Good | Acceptable | Illegal |
|---|---|---|---|---|
| Cluemaster 1.0 | 40 | 32% | 45% | 5% |
| Phi-4 Mini 3.8B | 11 | 5% | 27% | 36% |
| Granite 4.1 3B | 16 | 9% | 27% | 23% |
| Ministral 3 3B | 3 | 0% | 14% | 27% |
| Qwen 3.5 4B | 9 | 23% | 27% | 68% |
Endgame (3 or fewer of your words left)
| Model | Score | Good | Acceptable | Illegal |
|---|---|---|---|---|
| Cluemaster 1.0 | 67 | 54% | 74% | 3% |
| Phi-4 Mini 3.8B | 16 | 16% | 29% | 38% |
| Granite 4.1 3B | 23 | 16% | 34% | 24% |
| Ministral 3 3B | 5 | 7% | 19% | 38% |
| Qwen 3.5 4B | 1 | 15% | 18% | 65% |
Scoring
| Clue | Points on its board |
|---|---|
| Good | 100 |
| Ok | 70 |
| Bad, or no clue | 0 |
| Invalid: a target is a neutral word | โ10 |
| Invalid: a target is an opponent word | โ15 |
| Illegal, whatever it was rated | โ25 |
A segment scores 50% legal, 30% good and 20% acceptable, minus the penalties, never below zero. Cluebench is the mean of the three segments.
Use with Ollama
Put cluemaster-1.0-Q4_K_M.gguf and this Modelfile in one folder, then run ollama create cluemaster -f Modelfile.
FROM ./cluemaster-1.0-Q4_K_M.gguf
TEMPLATE """{{ if .System }}<s>[SYSTEM_PROMPT]{{ .System }}[/SYSTEM_PROMPT]{{ end }}{{ if .Prompt }}[INST]{{ .Prompt }}[/INST]{{ end }}{{ .Response }}</s>"""
PARAMETER stop <s>
PARAMETER stop [INST]
PARAMETER temperature 0.3
PARAMETER num_ctx 4096
For a full game with clue checks, use Cluemaster Studio: https://amandoti.win/cluemaster/studio.html
How to use it
The easy way: use Cluemaster Studio. Type in the board, press Get clue, and it handles the prompt and checks the clue against the rules.
Running it yourself: Cluemaster isn't a chat model. It does one job: you give it a board, and it gives you a clue.
Recommended system message:
You are a Codenames spymaster. Your teammate can see every word on the board but does not know which ones are yours. You give a one-word clue and a number: the number is how many of your team's words the clue points to.
The clue must not be a word on the board, or a form or part of one. Avoid clues that could lead your teammate to the opponent's words, the neutral words, or the assassin.
Recommended user message (put your own words in capitals):
BOARD
My team: BUNK, CENTER, BAND, SNAKE
Opponent: MAKEUP
Neutral: WELL, KITCHEN, STATE, HORSE
Assassin: MICROWAVE
Give a clue that connects 1 to 4 of your team's words. Connect 2 or 3 when there is a real link between them. If the words you have left have no good link, give a clue for a single word instead of forcing a weak pair.
Reply with your clue, the number, and the team words it connects, like this:
Clue: <one word>
Number: <how many team words it connects>
Words: <those team words, separated by commas>
What you get back:
Brainstorm:
- RUBBER: BAND, SNAKE. Found 2 of 2. Risk: WELL (neutral).
Clue: RUBBER
Number: 2
Words: BAND, SNAKE
Use the Clue, Number and Words lines. The brainstorm above them is its working. Set the temperature to about 0.3 and stop after 400 tokens, because it can keep writing extra answers after the first.
It only gives clues, so any other message gets a clue back.
Limits
- Midgame boards (4 or more of your words left) are its weakest case.
- About 4% of single answers are illegal, mostly by being or containing a board word. The Studio filters these out.
- Trained to give clues, not to guess. English only.
License
Apache 2.0, the same as the base model. This is a derivative of Ministral 3 3B Instruct by Mistral AI.
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Base model
mistralai/Ministral-3-3B-Base-2512