Safetensors
GGUF
English
intent-classification
decision-model
tool-routing
qwen3.5
unsloth
lora
conversational
Instructions to use cbarkinozer/Reflex-1 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 cbarkinozer/Reflex-1 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 cbarkinozer/Reflex-1:Q8_0 # Run inference directly in the terminal: llama cli -hf cbarkinozer/Reflex-1:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf cbarkinozer/Reflex-1:Q8_0 # Run inference directly in the terminal: llama cli -hf cbarkinozer/Reflex-1:Q8_0
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 cbarkinozer/Reflex-1:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf cbarkinozer/Reflex-1:Q8_0
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 cbarkinozer/Reflex-1:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf cbarkinozer/Reflex-1:Q8_0
Use Docker
docker model run hf.co/cbarkinozer/Reflex-1:Q8_0
- LM Studio
- Jan
- Ollama
How to use cbarkinozer/Reflex-1 with Ollama:
ollama run hf.co/cbarkinozer/Reflex-1:Q8_0
- Unsloth Desktop
- Pi
How to use cbarkinozer/Reflex-1 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf cbarkinozer/Reflex-1:Q8_0
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": "cbarkinozer/Reflex-1:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use cbarkinozer/Reflex-1 with Docker Model Runner:
docker model run hf.co/cbarkinozer/Reflex-1:Q8_0
- Lemonade
How to use cbarkinozer/Reflex-1 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull cbarkinozer/Reflex-1:Q8_0
Run and chat with the model
lemonade run user.Reflex-1-Q8_0
List all available models
lemonade list
- Hermes Agent
How to use cbarkinozer/Reflex-1 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf cbarkinozer/Reflex-1:Q8_0
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 cbarkinozer/Reflex-1:Q8_0
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use cbarkinozer/Reflex-1 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf cbarkinozer/Reflex-1:Q8_0
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 "cbarkinozer/Reflex-1:Q8_0" \ --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"
File size: 1,642 Bytes
d1111e5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"model": "reflex-1",
"state": "How much free storage is available on my phone?",
"questions": {
"route": {
"type": "choice",
"instructions": "Select exactly one route by the user's intended task. Route requests by meaning, including plausible future phone capabilities. Use phone_health_check for overall phone condition or requests spanning multiple live-data categories. Use answer for ordinary responses or when no stable tool intent can be inferred.",
"criteria": {
"answer": "General knowledge, arithmetic, writing, conversation, or a request requiring clarification because no stable tool intent is clear.",
"get_device_info": "Identify this device or inspect its OS, hardware specifications, capabilities, ratings, or certifications.",
"get_battery_info": "Inspect this phone's battery level, charging, temperature, health, usage, or runtime estimates.",
"get_storage_info": "Inspect this phone's storage space, usage, capacity, or internal or external storage status.",
"get_media_info": "Inspect current or recent media playback, metadata, availability, or playback settings.",
"search_local_files": "Find files on this device by name, type, content, time, location, or provenance.",
"search_notes": "Retrieve information or a note previously saved in the notes system.",
"save_note": "Store new information in the notes system when the user explicitly asks to save or remember it.",
"phone_health_check": "Inspect the phone's overall condition or readiness, or combine two or more live phone-data categories."
}
}
}
}
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