Instructions to use EditorAI-Geode/editorai-7b-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use EditorAI-Geode/editorai-7b-v3 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="EditorAI-Geode/editorai-7b-v3")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("EditorAI-Geode/editorai-7b-v3", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use EditorAI-Geode/editorai-7b-v3 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 EditorAI-Geode/editorai-7b-v3:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf EditorAI-Geode/editorai-7b-v3:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf EditorAI-Geode/editorai-7b-v3:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf EditorAI-Geode/editorai-7b-v3:Q4_K_M

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-7b-v3:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf EditorAI-Geode/editorai-7b-v3:Q4_K_M

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-7b-v3:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf EditorAI-Geode/editorai-7b-v3:Q4_K_M

Use Docker

docker model run hf.co/EditorAI-Geode/editorai-7b-v3:Q4_K_M

LM Studio
Jan

vLLM

How to use EditorAI-Geode/editorai-7b-v3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "EditorAI-Geode/editorai-7b-v3"
# 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-7b-v3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/EditorAI-Geode/editorai-7b-v3:Q4_K_M

SGLang

How to use EditorAI-Geode/editorai-7b-v3 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "EditorAI-Geode/editorai-7b-v3" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "EditorAI-Geode/editorai-7b-v3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "EditorAI-Geode/editorai-7b-v3" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "EditorAI-Geode/editorai-7b-v3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use EditorAI-Geode/editorai-7b-v3 with Ollama:
```
ollama run hf.co/EditorAI-Geode/editorai-7b-v3:Q4_K_M
```
Unsloth Desktop

How to use EditorAI-Geode/editorai-7b-v3 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf EditorAI-Geode/editorai-7b-v3: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": "EditorAI-Geode/editorai-7b-v3:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use EditorAI-Geode/editorai-7b-v3 with Docker Model Runner:
```
docker model run hf.co/EditorAI-Geode/editorai-7b-v3:Q4_K_M
```

Lemonade

How to use EditorAI-Geode/editorai-7b-v3 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull EditorAI-Geode/editorai-7b-v3:Q4_K_M

Run and chat with the model

lemonade run user.editorai-7b-v3-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use EditorAI-Geode/editorai-7b-v3 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf EditorAI-Geode/editorai-7b-v3: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 EditorAI-Geode/editorai-7b-v3:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use EditorAI-Geode/editorai-7b-v3 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf EditorAI-Geode/editorai-7b-v3: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 "EditorAI-Geode/editorai-7b-v3: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"

Entity12208 commited on May 31

Commit

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1 Parent(s): 2bfe268

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	@@ -0,0 +1,41 @@

+---
+license: apache-2.0
+base_model: Qwen/Qwen2.5-7B-Instruct
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- geometry-dash
+- gguf
+- llama-cpp
+- ollama
+- tool-use
+- geode
+- qwen2.5
+language:
+- en
+---
+# EditorAI v3 - 7B GD Level Designer with Tool Use
+Fine-tune of **Qwen/Qwen2.5-7B-Instruct** for the [EditorAI Geode mod](https://github.com/Entity12208/EditorAI).
+Major upgrade over v2 (1.5 B): reliable schema, frequent tool use, 32K context, full 3,986-object catalog.
+## Files
+| File | Size |
+|---|---|
+| `editorai-v3-Q4_K_M.gguf` | 4.46 GB (ship target) |
+| `Modelfile.v3` | Ollama Modelfile with 32K context + Qwen2.5 tool template |
+## Quick start
+```bash
+ollama pull entity12208/editorai:v3-7b
+# or build from this repo's files:
+ollama create entity12208/editorai:v3-7b -f Modelfile.v3
+```
+## Training
+QLoRA 4-bit NF4 on Qwen2.5-7B-Instruct, A100 40GB, 1 epoch (115 steps, ~58 min),
+3,700-row mixed dataset (2,000 level-gen from real .gmd + 1,200 multi-turn tool-use + 500 Alpaca).
+System prompt at training time matches the mod's runtime system prompt verbatim.
+License: Apache-2.0