Instructions to use EditorAI-Geode/editorai-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use EditorAI-Geode/editorai-mini with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="EditorAI-Geode/editorai-mini", filename="editorai-mini.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use EditorAI-Geode/editorai-mini with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf EditorAI-Geode/editorai-mini # Run inference directly in the terminal: llama-cli -hf EditorAI-Geode/editorai-mini
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf EditorAI-Geode/editorai-mini # Run inference directly in the terminal: llama-cli -hf EditorAI-Geode/editorai-mini
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 EditorAI-Geode/editorai-mini # Run inference directly in the terminal: ./llama-cli -hf EditorAI-Geode/editorai-mini
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 EditorAI-Geode/editorai-mini # Run inference directly in the terminal: ./build/bin/llama-cli -hf EditorAI-Geode/editorai-mini
Use Docker
docker model run hf.co/EditorAI-Geode/editorai-mini
- LM Studio
- Jan
- vLLM
How to use EditorAI-Geode/editorai-mini with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "EditorAI-Geode/editorai-mini" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "EditorAI-Geode/editorai-mini", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/EditorAI-Geode/editorai-mini
- Ollama
How to use EditorAI-Geode/editorai-mini with Ollama:
ollama run hf.co/EditorAI-Geode/editorai-mini
- Unsloth Studio new
How to use EditorAI-Geode/editorai-mini 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 EditorAI-Geode/editorai-mini 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 EditorAI-Geode/editorai-mini to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for EditorAI-Geode/editorai-mini to start chatting
- Pi new
How to use EditorAI-Geode/editorai-mini with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf EditorAI-Geode/editorai-mini
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": "EditorAI-Geode/editorai-mini" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use EditorAI-Geode/editorai-mini with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf EditorAI-Geode/editorai-mini
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 EditorAI-Geode/editorai-mini
Run Hermes
hermes
- Docker Model Runner
How to use EditorAI-Geode/editorai-mini with Docker Model Runner:
docker model run hf.co/EditorAI-Geode/editorai-mini
- Lemonade
How to use EditorAI-Geode/editorai-mini with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull EditorAI-Geode/editorai-mini
Run and chat with the model
lemonade run user.editorai-mini-{{QUANT_TAG}}List all available models
lemonade list
Upload README.md with huggingface_hub
Browse files
README.md
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license:
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---
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license: apache-2.0
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tags:
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- geometry-dash
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- level-generation
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- gguf
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- qwen2
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base_model: Qwen/Qwen2.5-0.5B-Instruct
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pipeline_tag: text-generation
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---
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# EditorAI Mini
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A fine-tuned Qwen2.5-0.5B-Instruct model that generates Geometry Dash levels as JSON.
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Trained on hand-crafted expert examples with triggers, groups, color channels, and proper GD level structure.
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## Usage with Ollama
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```bash
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# Download the GGUF
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# Place editorai-mini.gguf in a folder, create a Modelfile pointing to it
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ollama create entity12208/editorai:mini -f Modelfile
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ollama run entity12208/editorai:mini
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```
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## Usage with EditorAI Mod
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1. Install [EditorAI](https://github.com/Entity12208/EditorAI) for Geometry Dash (Geode mod)
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2. Set provider to **Ollama** and select `entity12208/editorai:mini`
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3. Generate levels!
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## Model Details
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- **Base model:** Qwen2.5-0.5B-Instruct
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- **Training:** QLoRA (4-bit, rank 8) on expert-crafted GD level examples
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- **Features:** Blocks, spikes, platforms, color triggers, move triggers, alpha triggers, rotate triggers, toggle triggers, pulse triggers, speed portals, groups, color channels
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- **GGUF quantization:** q4_k_m (379 MB)
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## Files
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- `model.safetensors` — merged fp16 model weights
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- `editorai-mini.gguf` — quantized GGUF (q4_k_m) for Ollama/llama.cpp
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- `Modelfile` — Ollama model definition with system prompt
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## License
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Apache 2.0
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