Text Generation
GGUF
English
Māori
llama.cpp
abteex-ai-labs
aotearoa
general
local-first
lumynax
new-zealand
qwen
sovereign-ai
text
vllm
vllm-compatible
vllm-experimental
nvidia-nim
nim-compatible
nim-candidate
nvidia-nemo
nem
nvidia-nemo-pathway
nem-pathway
nem-convert-required
legacy
outdated
conversational
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
- llama.cpp
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
- Pi
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"
| { | |
| "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, | |
| "ollama_create_script": "ollama/create_ollama_model.ps1", | |
| "ollama_modelfile": "ollama/Modelfile", | |
| "package_state": "merged_model/PACKAGE_STATE.txt", | |
| "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": { | |
| "reasoning_enabled": false, | |
| "supported_modalities": [ | |
| "text" | |
| ] | |
| }, | |
| "delivery": "standalone_prebuilt_gguf_release", | |
| "distribution": { | |
| "hf_space": { | |
| "app": "hf_space/app.py", | |
| "default_model_repo_id": "AbteeXAILab/lumynax-infused-qwen25-7b-instruct-gguf", | |
| "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": { | |
| "create_script": "ollama/create_ollama_model.ps1", | |
| "mmproj": null, | |
| "modelfile": "ollama/Modelfile", | |
| "preferred_gguf": "qwen2.5-7b-instruct-q3_k_m.gguf", | |
| "recommended_model_name": "lumynax-infused-qwen25-7b-instruct-gguf", | |
| "status": "ready_for_local_ollama_create" | |
| } | |
| }, | |
| "family": null, | |
| "generated_at": "2026-05-10T12:40:57.857697+00:00", | |
| "license": { | |
| "id": "apache-2.0", | |
| "link": "https://huggingface.co/Qwen/Qwen2.5-7B-Instruct-GGUF", | |
| "name": null, | |
| "weights_subject_to_upstream_license": true | |
| }, | |
| "manifest_version": 2, | |
| "model_title": "LumynaX Infused Qwen2.5 7B Instruct GGUF", | |
| "package_state": "prebuilt_gguf_release", | |
| "public_identity": { | |
| "model_name": "LumynaX", | |
| "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": { | |
| "filename": "qwen2.5-7b-instruct-q3_k_m.gguf", | |
| "mmproj_filename": null, | |
| "packaged_filename": "qwen2.5-7b-instruct-q3_k_m.gguf", | |
| "packaged_mmproj_filename": null, | |
| "quantization": "Q3_K_M", | |
| "repo_id": "Qwen/Qwen2.5-7B-Instruct-GGUF" | |
| }, | |
| "upstream_model": { | |
| "kind": "official_base_weights", | |
| "lumynax_weight_adaptation_applied": false, | |
| "provider": "Hugging Face", | |
| "repo_id": "Qwen/Qwen2.5-7B-Instruct" | |
| }, | |
| "lumynax_manifest_version": 3, | |
| "lifecycle": { | |
| "status": "legacy", | |
| "maintenance": "unmaintained", | |
| "production_recommended": false | |
| }, | |
| "lumynax_infusion": { | |
| "core_role": "primary_intelligence_model", | |
| "method": "routed", | |
| "infused_model": "Qwen/Qwen2.5-7B-Instruct", | |
| "weight_composition_applied": false, | |
| "moe_composition": "not_applied" | |
| }, | |
| "licensing": { | |
| "id": "apache-2.0", | |
| "license_file": "LICENSE.txt", | |
| "source_model_repo": "Qwen/Qwen2.5-7B-Instruct", | |
| "weights_subject_to_source_license": true | |
| } | |
| } | |