Instructions to use EditorAI-Geode/EditorAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use EditorAI-Geode/EditorAI with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="EditorAI-Geode/EditorAI", filename="editorai-latest.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use EditorAI-Geode/EditorAI 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 # Run inference directly in the terminal: llama-cli -hf EditorAI-Geode/EditorAI
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf EditorAI-Geode/EditorAI # Run inference directly in the terminal: llama-cli -hf EditorAI-Geode/EditorAI
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 # Run inference directly in the terminal: ./llama-cli -hf EditorAI-Geode/EditorAI
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 # Run inference directly in the terminal: ./build/bin/llama-cli -hf EditorAI-Geode/EditorAI
Use Docker
docker model run hf.co/EditorAI-Geode/EditorAI
- LM Studio
- Jan
- vLLM
How to use EditorAI-Geode/EditorAI with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "EditorAI-Geode/EditorAI" # 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", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/EditorAI-Geode/EditorAI
- Ollama
How to use EditorAI-Geode/EditorAI with Ollama:
ollama run hf.co/EditorAI-Geode/EditorAI
- Unsloth Studio new
How to use EditorAI-Geode/EditorAI 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 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 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 to start chatting
- Docker Model Runner
How to use EditorAI-Geode/EditorAI with Docker Model Runner:
docker model run hf.co/EditorAI-Geode/EditorAI
- Lemonade
How to use EditorAI-Geode/EditorAI with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull EditorAI-Geode/EditorAI
Run and chat with the model
lemonade run user.EditorAI-{{QUANT_TAG}}List all available models
lemonade list
Upload README.md with huggingface_hub
Browse files
README.md
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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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- tinyllama
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base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
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pipeline_tag: text-generation
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---
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# EditorAI
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The main EditorAI model — a fine-tuned TinyLlama-1.1B-Chat that generates Geometry Dash levels as JSON with blocks, spikes, platforms, triggers, groups, color channels, and more.
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Part of the [EditorAI](https://github.com/Entity12208/EditorAI) project — an AI-powered level generator mod for Geometry Dash.
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## About EditorAI
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[EditorAI](https://github.com/Entity12208/EditorAI) is a [Geode](https://geode-sdk.org) mod for Geometry Dash that lets you describe a level in plain text and have AI build it in the editor. It supports 8 AI providers (Gemini, Claude, OpenAI, Mistral, HuggingFace, Ollama, LM Studio, llama.cpp) and features blueprint preview, feedback learning, 15+ trigger types, and an in-game settings UI.
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## Model Details
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- **Base model:** TinyLlama-1.1B-Chat-v1.0
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- **Training:** QLoRA (4-bit, rank 8) on 2368 examples (368 expert-crafted + 2000 synthetic), 2 epochs
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- **Features:** Blocks, spikes, platforms, color triggers, move triggers, alpha triggers, rotate triggers, toggle triggers, pulse triggers, spawn triggers, stop triggers, speed portals, groups, color channels
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- **GGUF quantization:** q4_k_m (637 MB)
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- **Tested:** 8/8 tests passed, generates all trigger types
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## Files
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| File | Size | Description |
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|------|------|-------------|
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| `model.safetensors` | 2.1 GB | Merged fp16 model weights |
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| `editorai-latest.gguf` | 637 MB | Quantized GGUF (q4_k_m) for llama.cpp / LM Studio |
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| `config.json` | — | Model architecture config |
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| `tokenizer.json` | — | Tokenizer |
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## Setup
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This model uses the **Zephyr/ChatML** chat template and works best with the following system prompt:
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```
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You are a Geometry Dash level designer. Return ONLY valid JSON with an analysis string and objects array. Each object needs type, x, y. Y >= 0. X uses 10 units per grid cell.
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```
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> **Recommended:** Use the Ollama version (`entity12208/editorai:latest`) which has the system prompt and template pre-configured.
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## Usage with llama.cpp
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```bash
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wget https://huggingface.co/EditorAI-Geode/EditorAI/resolve/main/editorai-latest.gguf
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llama-server -m editorai-latest.gguf --port 8080 --chat-template chatml
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# In the EditorAI mod: set provider to "llama-cpp", URL to http://localhost:8080
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```
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## Usage with LM Studio
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1. Download `editorai-latest.gguf` from this repo
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2. Load it in LM Studio, set **Prompt Format** to **ChatML**
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3. Set the **System Prompt** to the prompt above
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4. Start the server
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5. In the EditorAI mod: set provider to "lm-studio", URL to `http://localhost:1234`
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## Usage with Ollama (recommended)
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```bash
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ollama pull entity12208/editorai:latest
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```
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In the EditorAI mod: set provider to "ollama" and select `entity12208/editorai:latest`.
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## Output Format
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```json
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{
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"analysis": "A medium modern level with color transitions and moving platforms.",
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"objects": [
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{"type": "block_black_gradient_square", "x": 0, "y": 0, "color_channel": 10},
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{"type": "spike_black_gradient_spike", "x": 50, "y": 0},
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{"type": "color_trigger", "x": 80, "y": 0, "color_channel": 1, "color": "#0066FF", "duration": 1.5},
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{"type": "move_trigger", "x": 90, "y": 0, "target_group": 1, "move_x": 0, "move_y": 20, "duration": 1.0, "easing": 1},
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{"type": "end_trigger", "x": 400, "y": 0}
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]
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}
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```
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## Model Comparison
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| Model | Size | Triggers | Quality | Speed |
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|-------|------|----------|---------|-------|
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| **editorai:latest** (this) | 637 MB | All types | Best | ~15-30s |
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| editorai:mini | 379 MB | Color, move | Good | ~10-20s |
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## Links
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- **Mod:** [github.com/Entity12208/EditorAI](https://github.com/Entity12208/EditorAI)
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- **Ollama:** [ollama.com/entity12208/editorai](https://ollama.com/entity12208/editorai)
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- **Mini model:** [huggingface.co/EditorAI-Geode/editorai-mini](https://huggingface.co/EditorAI-Geode/editorai-mini)
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- **Discord:** [discord.gg/5hwCqMUYNj](https://discord.gg/5hwCqMUYNj)
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## License
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Apache 2.0
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