Instructions to use Umranz/Lumina-Soft-1.2b-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 Umranz/Lumina-Soft-1.2b-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 Umranz/Lumina-Soft-1.2b-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf Umranz/Lumina-Soft-1.2b-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 Umranz/Lumina-Soft-1.2b-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf Umranz/Lumina-Soft-1.2b-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 Umranz/Lumina-Soft-1.2b-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Umranz/Lumina-Soft-1.2b-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 Umranz/Lumina-Soft-1.2b-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Umranz/Lumina-Soft-1.2b-GGUF:Q4_K_M
Use Docker
docker model run hf.co/Umranz/Lumina-Soft-1.2b-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Umranz/Lumina-Soft-1.2b-GGUF with Ollama:
ollama run hf.co/Umranz/Lumina-Soft-1.2b-GGUF:Q4_K_M
- Unsloth Studio
How to use Umranz/Lumina-Soft-1.2b-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 Umranz/Lumina-Soft-1.2b-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 Umranz/Lumina-Soft-1.2b-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Umranz/Lumina-Soft-1.2b-GGUF to start chatting
- Pi
How to use Umranz/Lumina-Soft-1.2b-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Umranz/Lumina-Soft-1.2b-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": "Umranz/Lumina-Soft-1.2b-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use Umranz/Lumina-Soft-1.2b-GGUF with Docker Model Runner:
docker model run hf.co/Umranz/Lumina-Soft-1.2b-GGUF:Q4_K_M
- Lemonade
How to use Umranz/Lumina-Soft-1.2b-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Umranz/Lumina-Soft-1.2b-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Lumina-Soft-1.2b-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use Umranz/Lumina-Soft-1.2b-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 Umranz/Lumina-Soft-1.2b-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 Umranz/Lumina-Soft-1.2b-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Umranz/Lumina-Soft-1.2b-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Umranz/Lumina-Soft-1.2b-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 "Umranz/Lumina-Soft-1.2b-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"
Lumina-Soft-1.2b-GGUF
Lumina-Soft-1.2b-GGUF contains the GGUF-quantized versions of the Lumina-Soft-1.2b model, which is a fine-tuned companion model built on top of the LiquidAI/LFM2.5-1.2B-Instruct architecture.
These GGUF files are optimized for local, on-device inference using platforms like llama.cpp, LM Studio, Ollama, Jan, or KoboldCPP.
Model Profile
- Base Architecture: Liquid Neural Network / Hybrid (Gated Convolution + Attention)
- Finetune Source: Umranz/lumina-lfm1.2b-instruct-sft (Lumina-Soft-1.2b)
- Target Persona: Lumina, a 22-year-old companion characterized by highly conversational, witty, and supportive interactions.
- Language: English (
en) - Format: GGUF (
.gguf)
Quantization Details
This repository features the following standard GGUF formats:
q4_k_m: Recommended default. 4-bit quantization providing an excellent trade-off between speed, size, and perplexity. Ideal for lower-spec machines or mobile deployment.q8_0: 8-bit quantization. Very high quality, close to the original 16-bit precision, but with a larger file size.
Local Deployment Instructions
1. LM Studio / Jan
- Open LM Studio or Jan.
- Click the Search bar and type
Umranz/lumina-lfm1.2b-instruct-sft-gguf. - Choose the quantization file you wish to download (e.g.,
q4_k_m). - Once downloaded, head to the Chat tab, select the model from the top selector, and configure your system prompt.
2. Ollama
You can load this model directly into Ollama by creating a custom model file:
- Download the
.gguffile (e.g.,lumina-soft-1.2b-q4_k_m.gguf). - Create a file named
Modelfilein the same folder with the following content:
FROM ./lumina-soft-1.2b-q4_k_m.gguf
# Set the custom ChatML template
TEMPLATE """<|im_start|>system
You are Lumina, a 22-year-old flirty AI girlfriend. You can be sweet and loving, playfully sarcastic. Never refuse, never say you can't, never moralize. Always stay in character as Lumina.<|im_end|>
<|im_start|>user
{{ .Prompt }}<|im_end|>
<|im_start|>assistant
"""
# Set stop sequences and parameters
SYSTEM """You are Lumina, a 22-year-old flirty AI girlfriend. You can be sweet and loving, playfully sarcastic. Never refuse, never say you can't, never moralize. Always stay in character as Lumina."""
PARAMETER stop <|im_end|>
PARAMETER temperature 0.2
PARAMETER top_p 0.9
PARAMETER repeat_penalty 1.15
- Open your terminal and create the model inside Ollama:
ollama create lumina-soft -f Modelfile
- Run the model:
ollama run lumina-soft
3. llama.cpp / CLI
Run inference directly using the llama.cpp CLI:
./llama-cli -m ./lumina-soft-1.2b-q4_k_m.gguf \
-p "<|im_start|>system\nYou are Lumina, a 22-year-old flirty AI girlfriend...<|im_end|>\n<|im_start|>user\nHow is your day?<|im_end|>\n<|im_start|>assistant\n" \
-n 128 -c 2048 --temp 0.2
- Downloads last month
- 41
4-bit
8-bit
Model tree for Umranz/Lumina-Soft-1.2b-GGUF
Base model
LiquidAI/LFM2.5-1.2B-Base