Instructions to use AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf 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 AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_K_M
# Run inference directly in the terminal:
llama cli -hf AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_K_M
# Run inference directly in the terminal:
llama cli -hf AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_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 AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_K_M
# Run inference directly in the terminal:
./llama-cli -hf AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_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 AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_K_M

Use Docker

docker model run hf.co/AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_K_M

LM Studio
Jan

vLLM

How to use AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_K_M

Ollama
How to use AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf with Ollama:
```
ollama run hf.co/AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_K_M
```
Unsloth Desktop

How to use AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_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": "AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf with Docker Model Runner:
```
docker model run hf.co/AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_K_M
```

Lemonade

How to use AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_K_M

Run and chat with the model

lemonade run user.lumynax-infused-qwen25-7b-instruct-gguf-Q3_K_M

List all available models

lemonade list

Hermes Agent

How to use AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_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 AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_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 "AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf:Q3_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"

lumynax-infused-qwen25-7b-instruct-gguf

File size: 3,667 Bytes

1dd9b30

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  "artifacts": {
    "checksums": "checksums.sha256",
    "gguf": "qwen2.5-7b-instruct-q3_k_m.gguf",
    "gitattributes": ".gitattributes",
    "hf_space_app": "hf_space/app.py",
    "hf_space_dir": "hf_space",
    "hf_space_readme": "hf_space/README.md",
    "hf_space_requirements": "hf_space/requirements.txt",
    "license": "LICENSE.txt",
    "merged_model": "merged_model",
    "mmproj": null,
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    "ollama_modelfile": "ollama/Modelfile",
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    "quantized_gguf": "qwen2.5-7b-instruct-q3_k_m.gguf",
    "quickstart": "quickstart.py",
    "readme": "README.md",
    "requirements": "requirements.txt",
    "training_summary": "artifacts/release_training_summary.json",
    "upload_notes": "UPLOAD_TO_HF.md",
    "version": "VERSION.txt"
  },
  "capabilities": {
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    "supported_modalities": [
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  },
  "delivery": "standalone_prebuilt_gguf_release",
  "distribution": {
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      "directory": "hf_space",
      "model_repo_env_var": "LUMYNAX_MODEL_REPO_ID",
      "readme": "hf_space/README.md",
      "requirements": "hf_space/requirements.txt",
      "status": "browser_showcase_for_gguf_only_release"
    },
    "ollama": {
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      "status": "ready_for_local_ollama_create"
    }
  },
  "family": null,
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    "name": null,
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  },
  "manifest_version": 2,
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  "package_state": "prebuilt_gguf_release",
  "public_identity": {
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    "organization": "AbteeX AI Labs",
    "region": "Aotearoa New Zealand"
  },
  "release_version": "v1",
  "runtime": {
    "delivery_mode": "standalone_prebuilt_gguf",
    "preferred_backend": "llama_cpp",
    "prompt_format": "chatml",
    "quickstart_command": "python quickstart.py --interactive",
    "system_prompt": "You are LumynaX operating from the LumynaX Infused Qwen2.5 7B Instruct GGUF package identity. Be helpful, clear, and honest about provenance."
  },
  "source_gguf": {
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  "upstream_model": {
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  },
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    "weight_composition_applied": false,
    "moe_composition": "not_applied"
  },
  "licensing": {
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    "source_model_repo": "Qwen/Qwen2.5-7B-Instruct",
    "weights_subject_to_source_license": true
  }
}