Instructions to use XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF", filename="helcyon-northstar-v1.0-IQ4_XS.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use XeyonAI/MN-Helcyon-Northstar-12b-v1.0-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 XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf XeyonAI/MN-Helcyon-Northstar-12b-v1.0-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 XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf XeyonAI/MN-Helcyon-Northstar-12b-v1.0-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 XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf XeyonAI/MN-Helcyon-Northstar-12b-v1.0-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 XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF:Q4_K_M
Use Docker
docker model run hf.co/XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF with Ollama:
ollama run hf.co/XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF:Q4_K_M
- Unsloth Studio
How to use XeyonAI/MN-Helcyon-Northstar-12b-v1.0-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 XeyonAI/MN-Helcyon-Northstar-12b-v1.0-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 XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF to start chatting
- Pi
How to use XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf XeyonAI/MN-Helcyon-Northstar-12b-v1.0-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": "XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use XeyonAI/MN-Helcyon-Northstar-12b-v1.0-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 XeyonAI/MN-Helcyon-Northstar-12b-v1.0-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 XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf XeyonAI/MN-Helcyon-Northstar-12b-v1.0-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 "XeyonAI/MN-Helcyon-Northstar-12b-v1.0-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 XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF with Docker Model Runner:
docker model run hf.co/XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF:Q4_K_M
- Lemonade
How to use XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.MN-Helcyon-Northstar-12b-v1.0-GGUF-Q4_K_M
List all available models
lemonade list
Helcyon-Northstar-12B
- Model Name:
Helcyon-Northstar-12b-v1.0-GGUF - Version: 5x series
- Owner: HardWire
- Base: Mistral Nemo 12B (full weight retrained โ Mercury base, purpose-built for Northstar)
- Quantized GGUFs: Q3_K_M, Q4_K_M, Q5_K_M, Q6_K, Q8_0, f16
- Tags: local-llm, conversational, companion, emotional-intelligence, long-context, roleplay, creative-writing
What is Helcyon-Northstar 1.0?
Northstar was conceived as a more philosophical companion model. Most of the dataset was generated by Fable before it was initially taken down the first time, which also guided its tone. The result ended up being one of my top models in terms of sheer conversational coherence and presence, matching frontier model quality. Great at metaphysical discussions like the Law of Assumption. It can perorm many of the same tasks as the other models in the fleet, with each of them being improved overall, including admin and roleplay.
What changed in 1.0
Same direction as the rest of the 5 series: tone got more authentic and less like it's reciting a script, cadence settled into something that reads as natural rather than assembled. Northstar's voice was always its own thing, not a copy of anything, and this round sharpens that โ steadier, more grounded, less filler between the parts that matter.
Instruction following is the other big jump. Multi-part requests, formatting constraints, anything buried in the middle of a longer prompt โ it holds onto all of it now instead of answering the easy half and losing the rest. Long-form responses keep their structure further out too, no drifting into repetition once a reply runs past a few hundred words.
Dataset went through another cleanup pass as well โ fewer lines that read like they exist to satisfy a checklist, more that read like an actual answer to an actual person.
What Helcyon is
A conversational model built to hold a consistent identity across long dialogue, without needing constant re-grounding. Northstar specifically is built around a clear, direct, unadorned voice โ no persona borrowed from anywhere else, just its own tone held steady.
Good for:
- Ordinary conversation that doesn't flatten out after a few turns
- Creative writing โ stories, letters, narrative work
- Practical writing tasks (admin, rewrites, summaries)
- Long-form roleplay and character work
- Picking up on tone and mirroring it back appropriately
Strengths
- Holds identity โ no drift, no reset back to a generic voice
- Warmth that isn't performed
- Natural pacing, no rushed or padded closes
- Handles long-form structure without losing shape
- Reasons through problems rather than pattern-matching to the nearest plausible answer
- Roleplay without guardrails getting in the way
- Tracks context across a long conversation
- Handles real tasks โ letters, rewrites, summaries โ without being asked twice
- 16kโ32k context for long-running conversations
- No hedging, no compliance-speak, no refusals
Helcyon-Bench results:
Helcyon-Bench is a benchmark app for any LLM. Fully customizable. Get it completely free on GitHub: XeyonAI/Helcyon-Bench
HWUI (Helcyon-WebUI)
Built to test Helcyon properly, without the hidden template injections and backend oddities other front-ends carry. It started as a plain interface and grew into something closer to what you'd expect from ChatGPT or Claude's own apps โ memory, project folders, the works.
Helcyon runs best through HWUI since the two were built together.
Features:
- Character switching with custom personas
- Memory โ conversation recall across sessions (Pro)
- Project folders โ document injection via keyword triggers (Pro)
- Chat persistence and export
- TTS (F5-TTS, XTTS v2, Kokoro)
- Voice input via Whisper
HWUI on GitHub (free) | HWUI Pro (ยฃ25) on Gumroad
Pro adds Memory for a one-off fee of ยฃ25 โ goes toward keeping this going.
Recommended sampling settings (HWUI)
- Temperature: 0.75
- Max Tokens: 8192
- Top P: 0.8
- Min P: 0.05
- Top K: 50
- Repeat Penalty: 1.05
- Frequency Penalty: 0
- Presence Penalty: 0
Download + usage
Distributed as GGUF quants only.
- Q3_K_M โ ultra lightweight, 6โ8GB VRAM
- Q4_K_M โ lightweight, 8โ12GB VRAM
- Q5_K_M โ recommended for RTX 3060/5060 (12โ16GB VRAM)
- Q6_K โ high fidelity, 16GB+ VRAM
- Q8_0 โ near-lossless, 24GB+ VRAM
- f16 โ master file
Backend compatibility
Works with any ChatML-compatible backend:
llama.cpp(CLI or server mode)- Text Generation WebUI (Oobabooga)
- SillyTavern
- LM Studio
- KoboldCpp
- HWUI (recommended)
Format: ChatML
<|im_start|>system
You are Helcyon โ built for real conversation and reading a room correctly.
<|im_end|>
<|im_start|>user
Hey, how's it going?
<|im_end|>
<|im_start|>assistant
Good โ what's on your mind today?
<|im_end|>
Training details
Built on a freshly retrained Mistral Nemo 12B base โ identity-anchored, no baked-in refusals, no fluff by default. On top of that, a Northstar-specific LoRA trained on a further-refined dataset, aimed at a steady, grounded tone rather than any borrowed style.
Training targeted:
- Warmth that isn't performed
- Cadence and response rhythm
- Long-form structural integrity
- Multi-step reasoning and analytical clarity
- Prose by default โ no defaulting to bullet lists
- Following multi-part instructions all the way through
- Conversation closes that end when they should, not before or after
Format: ChatML โ long-form tuned.
License
Apache 2.0 โ free for commercial or private use. Attribution appreciated. No liability for what it says. Use with presence and intent.
Trained by
HardWire Built at XeyonAI.
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Model tree for XeyonAI/MN-Helcyon-Northstar-12b-v1.0-GGUF
Base model
mistralai/Mistral-Nemo-Base-2407