GGUF
pollard-weights
connectome
memory
long-context
associative-memory
flybrain
pollard
imatrix
conversational
Instructions to use PollardWeights/FlyBrain-Pollard-CNSv1 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 PollardWeights/FlyBrain-Pollard-CNSv1 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 PollardWeights/FlyBrain-Pollard-CNSv1:IQ3_S # Run inference directly in the terminal: llama cli -hf PollardWeights/FlyBrain-Pollard-CNSv1:IQ3_S
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf PollardWeights/FlyBrain-Pollard-CNSv1:IQ3_S # Run inference directly in the terminal: llama cli -hf PollardWeights/FlyBrain-Pollard-CNSv1:IQ3_S
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 PollardWeights/FlyBrain-Pollard-CNSv1:IQ3_S # Run inference directly in the terminal: ./llama-cli -hf PollardWeights/FlyBrain-Pollard-CNSv1:IQ3_S
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 PollardWeights/FlyBrain-Pollard-CNSv1:IQ3_S # Run inference directly in the terminal: ./build/bin/llama-cli -hf PollardWeights/FlyBrain-Pollard-CNSv1:IQ3_S
Use Docker
docker model run hf.co/PollardWeights/FlyBrain-Pollard-CNSv1:IQ3_S
- LM Studio
- Jan
- Ollama
How to use PollardWeights/FlyBrain-Pollard-CNSv1 with Ollama:
ollama run hf.co/PollardWeights/FlyBrain-Pollard-CNSv1:IQ3_S
- Unsloth Desktop
- Pi
How to use PollardWeights/FlyBrain-Pollard-CNSv1 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf PollardWeights/FlyBrain-Pollard-CNSv1:IQ3_S
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": "PollardWeights/FlyBrain-Pollard-CNSv1:IQ3_S" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use PollardWeights/FlyBrain-Pollard-CNSv1 with Docker Model Runner:
docker model run hf.co/PollardWeights/FlyBrain-Pollard-CNSv1:IQ3_S
- Lemonade
How to use PollardWeights/FlyBrain-Pollard-CNSv1 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull PollardWeights/FlyBrain-Pollard-CNSv1:IQ3_S
Run and chat with the model
lemonade run user.FlyBrain-Pollard-CNSv1-IQ3_S
List all available models
lemonade list
- Hermes Agent
How to use PollardWeights/FlyBrain-Pollard-CNSv1 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf PollardWeights/FlyBrain-Pollard-CNSv1:IQ3_S
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 PollardWeights/FlyBrain-Pollard-CNSv1:IQ3_S
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use PollardWeights/FlyBrain-Pollard-CNSv1 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf PollardWeights/FlyBrain-Pollard-CNSv1:IQ3_S
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 "PollardWeights/FlyBrain-Pollard-CNSv1:IQ3_S" \ --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"
Commit History
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Card: rung guide with measured per-layer allocation and KL cliff
Verified signaturea75edff
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Pollard quant ladder: Qwen2.5-0.5B-Instruct-Pollard-Q6_K.gguf
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Pollard quant ladder: Qwen2.5-0.5B-Instruct-Pollard-IQ4_XS.gguf
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Pollard quant ladder: Qwen2.5-0.5B-Instruct-Pollard-IQ3_S.gguf
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Drop the vendored tool copies -- the code lives in pollard-weights, not here
Verified signatureA model repo should hold the artifact and its card. The loader and the verifier are part of the pollard-weights package and go stale the moment they are copied; the card installs them with pip instead.78baadf -
Replace with the verified brain: 100% exact recall, floor 0%, both controls 0%
Verified signatureOld artifact and card were the pre-rebuild architecture (loss-based '97.4% of the gap', 0.03 MB state). This is the current brain: 128-sample exact verbatim recall at 100%, floor 0%, both leakage controls 0%, 11.2 MB constant state. Stale standalone loaders removed -- they cannot read a current checkpoint. Adds pollard_brainverify.py, which carries the correct measurement construction.24ac23a
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flybrain: accept lists as well as numpy arrays in the constructor
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add flybrain.py
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add README.md
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add flybrain_state.py
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add FlyBrain-Pollard-CNSv1.pt
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initial commit
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