Instructions to use MicroFlare/nanoFlare-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use MicroFlare/nanoFlare-v1 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 MicroFlare/nanoFlare-v1
# Run inference directly in the terminal:
llama cli -hf MicroFlare/nanoFlare-v1

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf MicroFlare/nanoFlare-v1
# Run inference directly in the terminal:
llama cli -hf MicroFlare/nanoFlare-v1

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 MicroFlare/nanoFlare-v1
# Run inference directly in the terminal:
./llama-cli -hf MicroFlare/nanoFlare-v1

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 MicroFlare/nanoFlare-v1
# Run inference directly in the terminal:
./build/bin/llama-cli -hf MicroFlare/nanoFlare-v1

Use Docker

docker model run hf.co/MicroFlare/nanoFlare-v1

LM Studio
Jan
Ollama
How to use MicroFlare/nanoFlare-v1 with Ollama:
```
ollama run hf.co/MicroFlare/nanoFlare-v1
```

Unsloth Studio

How to use MicroFlare/nanoFlare-v1 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 MicroFlare/nanoFlare-v1 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 MicroFlare/nanoFlare-v1 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for MicroFlare/nanoFlare-v1 to start chatting

How to use MicroFlare/nanoFlare-v1 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf MicroFlare/nanoFlare-v1

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": "MicroFlare/nanoFlare-v1"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use MicroFlare/nanoFlare-v1 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf MicroFlare/nanoFlare-v1

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 "MicroFlare/nanoFlare-v1" \
  --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 MicroFlare/nanoFlare-v1 with Docker Model Runner:
```
docker model run hf.co/MicroFlare/nanoFlare-v1
```

Lemonade

How to use MicroFlare/nanoFlare-v1 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull MicroFlare/nanoFlare-v1

Run and chat with the model

lemonade run user.nanoFlare-v1-{{QUANT_TAG}}

List all available models

lemonade list

Hermes Agent

How to use MicroFlare/nanoFlare-v1 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf MicroFlare/nanoFlare-v1

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 MicroFlare/nanoFlare-v1

Run Hermes

hermes

Atomic Chat

nanoFlare is my newest model, based on the just released Qwen 3.8 27B. The version available currently is an early preview build, note it still has some kinks to work out. Sometimes it will work fine and sometimes it gets caught in thinking loops and makes mistakes.

This beta version is not recommended for anything other than expirmental use currently. New revisions will be coming soon that hopefully fix all the issues.

nanoFlare is designed to run completely on GPU if you have 8GB of VRAM, otherwise it can be ran on CPU if you have at least 8GB or more of system memory.

No testing has been performed yet.

Downloads last month: 183

GGUF

Model size

27B params

Architecture

qwen35

Hardware compatibility

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