Instructions to use ales27pm/lumen-qwen3-bootstrap-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 ales27pm/lumen-qwen3-bootstrap-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 ales27pm/lumen-qwen3-bootstrap-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ales27pm/lumen-qwen3-bootstrap-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf ales27pm/lumen-qwen3-bootstrap-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ales27pm/lumen-qwen3-bootstrap-gguf: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 ales27pm/lumen-qwen3-bootstrap-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf ales27pm/lumen-qwen3-bootstrap-gguf: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 ales27pm/lumen-qwen3-bootstrap-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ales27pm/lumen-qwen3-bootstrap-gguf:Q4_K_M

Use Docker

docker model run hf.co/ales27pm/lumen-qwen3-bootstrap-gguf:Q4_K_M

LM Studio
Jan

vLLM

How to use ales27pm/lumen-qwen3-bootstrap-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ales27pm/lumen-qwen3-bootstrap-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": "ales27pm/lumen-qwen3-bootstrap-gguf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ales27pm/lumen-qwen3-bootstrap-gguf:Q4_K_M

Ollama
How to use ales27pm/lumen-qwen3-bootstrap-gguf with Ollama:
```
ollama run hf.co/ales27pm/lumen-qwen3-bootstrap-gguf:Q4_K_M
```

Unsloth Studio

How to use ales27pm/lumen-qwen3-bootstrap-gguf 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 ales27pm/lumen-qwen3-bootstrap-gguf 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 ales27pm/lumen-qwen3-bootstrap-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for ales27pm/lumen-qwen3-bootstrap-gguf to start chatting

How to use ales27pm/lumen-qwen3-bootstrap-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ales27pm/lumen-qwen3-bootstrap-gguf:Q4_K_M

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": "ales27pm/lumen-qwen3-bootstrap-gguf:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use ales27pm/lumen-qwen3-bootstrap-gguf with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ales27pm/lumen-qwen3-bootstrap-gguf: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 "ales27pm/lumen-qwen3-bootstrap-gguf: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"

Docker Model Runner
How to use ales27pm/lumen-qwen3-bootstrap-gguf with Docker Model Runner:
```
docker model run hf.co/ales27pm/lumen-qwen3-bootstrap-gguf:Q4_K_M
```

Lemonade

How to use ales27pm/lumen-qwen3-bootstrap-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ales27pm/lumen-qwen3-bootstrap-gguf:Q4_K_M

Run and chat with the model

lemonade run user.lumen-qwen3-bootstrap-gguf-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use ales27pm/lumen-qwen3-bootstrap-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 ales27pm/lumen-qwen3-bootstrap-gguf: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 ales27pm/lumen-qwen3-bootstrap-gguf:Q4_K_M

Run Hermes

hermes

Atomic Chat

lumen-qwen3-bootstrap-gguf / README.md

ales27pm

Clarify shared-base artifact lineage scope (#2)

903587d 3 days ago

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metadata

language:
  - en
library_name: llama.cpp
pipeline_tag: text-generation
tags:
  - gguf
  - qwen3
  - quantized
  - on-device
  - lumen
base_model:
  - Qwen/Qwen3-1.7B

Lumen Qwen3 1.7B shared-base GGUF

This card documents the single shared-base artifact lumen-qwen3-fast-shared-q4_k_m.gguf in ales27pm/lumen-qwen3-bootstrap-gguf. Lumen uses it as the common base for role-specific LoRA adapters in its local-first iOS runtime.

Immutable artifact identity

Field	Value
Lumen repository	`ales27pm/lumen-qwen3-bootstrap-gguf`
Lumen artifact lineage revision	`8abae6d695408dbc75a134212dd616cd14549ae1`
Lumen file	`lumen-qwen3-fast-shared-q4_k_m.gguf`
File size	1,282,439,264 bytes
File SHA-256	`a7f6720f68f4a4567ebf7e3257041dd0b72077b518efe56890aec3516b59b9de`
Immediate source repository	`rippertnt/Qwen3-1.7B-Q4_K_M-GGUF`
Immediate source revision	`b93c0c328252f68cda622847ba0218689a8b6ba4`
Immediate source file	`qwen3-1.7b-q4_k_m.gguf`
Identified upstream base	`Qwen/Qwen3-1.7B`
Exact upstream Qwen revision used for quantization	Not recorded

Pinned links: Lumen artifact, immediate-source artifact, and immediate-source card.

The Lumen file is byte-identical to the immediate-source file at the pinned revision. Lumen only renamed and re-hosted that GGUF; it did not convert, quantize, merge, or otherwise modify its bytes.

The immediate-source model card identifies Qwen/Qwen3-1.7B as the base, declares Apache-2.0, and describes GGUF conversion with llama.cpp through the GGUF-my-repo workflow. It does not record the immutable upstream Qwen commit used for the April 2025 conversion, so this card does not invent one.

Scope warning

This card's byte-identity and provenance statements apply only to lumen-qwen3-fast-shared-q4_k_m.gguf. The artifact-lineage revision also contains separate Lumen release-bake GGUF files. Those files are not the byte-identical rehost documented here, and this card does not establish their provenance or license status. They require separate documentation before any repository-wide licensing claim is made.

Intended use

The covered artifact is intended as a local GGUF base for a compatible llama.cpp runtime, including Lumen's role-adapter runtime. Model output is untrusted and must remain behind application-layer validation, permissions, approvals, privacy controls, and bounded tool execution.

Limitations

The exact upstream Qwen/Qwen3-1.7B revision used by the immediate-source quantizer is unknown.
Quality, safety, and performance depend on the runtime, prompt, sampling configuration, device, and any applied adapters.
This artifact is not itself an application safety or authorization system.

License and attribution

The covered shared-base artifact is provided under the Apache License 2.0; see LICENSE. See NOTICE.md for the immutable source chain, modification statement, scope boundary, and attribution.

Alibaba Cloud, the Qwen authors, rippertnt, Hugging Face, llama.cpp, GGUF-my-repo, and their respective contributors do not endorse Lumen, this rehost, or applications that use it.