Instructions to use SoulInPsyAbstract/protocol0-llama-3.1-8b-v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use SoulInPsyAbstract/protocol0-llama-3.1-8b-v5 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 SoulInPsyAbstract/protocol0-llama-3.1-8b-v5:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf SoulInPsyAbstract/protocol0-llama-3.1-8b-v5:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf SoulInPsyAbstract/protocol0-llama-3.1-8b-v5:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf SoulInPsyAbstract/protocol0-llama-3.1-8b-v5: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 SoulInPsyAbstract/protocol0-llama-3.1-8b-v5:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf SoulInPsyAbstract/protocol0-llama-3.1-8b-v5: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 SoulInPsyAbstract/protocol0-llama-3.1-8b-v5:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf SoulInPsyAbstract/protocol0-llama-3.1-8b-v5:Q4_K_M

Use Docker

docker model run hf.co/SoulInPsyAbstract/protocol0-llama-3.1-8b-v5:Q4_K_M

LM Studio
Jan
Ollama
How to use SoulInPsyAbstract/protocol0-llama-3.1-8b-v5 with Ollama:
```
ollama run hf.co/SoulInPsyAbstract/protocol0-llama-3.1-8b-v5:Q4_K_M
```
Unsloth Desktop

How to use SoulInPsyAbstract/protocol0-llama-3.1-8b-v5 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf SoulInPsyAbstract/protocol0-llama-3.1-8b-v5:Q4_K_M

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": "SoulInPsyAbstract/protocol0-llama-3.1-8b-v5:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use SoulInPsyAbstract/protocol0-llama-3.1-8b-v5 with Docker Model Runner:
```
docker model run hf.co/SoulInPsyAbstract/protocol0-llama-3.1-8b-v5:Q4_K_M
```

Lemonade

How to use SoulInPsyAbstract/protocol0-llama-3.1-8b-v5 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull SoulInPsyAbstract/protocol0-llama-3.1-8b-v5:Q4_K_M

Run and chat with the model

lemonade run user.protocol0-llama-3.1-8b-v5-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use SoulInPsyAbstract/protocol0-llama-3.1-8b-v5 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf SoulInPsyAbstract/protocol0-llama-3.1-8b-v5: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 SoulInPsyAbstract/protocol0-llama-3.1-8b-v5:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use SoulInPsyAbstract/protocol0-llama-3.1-8b-v5 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf SoulInPsyAbstract/protocol0-llama-3.1-8b-v5: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 "SoulInPsyAbstract/protocol0-llama-3.1-8b-v5: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"

protocol0-llama-3.1-8b-v5

Fine-tuned meta-llama/Llama-3.1-8B-Instruct on the protocol0 behavioral compliance dataset (v5, 2,349 examples), part of the SIPA OS AI experiment series (https://github.com/soulinpsyabstract/sipa-os-governance/tree/main/AI_EXPERIMENTS).

The dataset trains the model toward a specific set of behavioral constraints — stopping under ambiguity, not fabricating unverifiable claims, no unsolicited opinions, single-action responses, conciseness — derived from an internal governance protocol (Protocol 0 / CORE LAW), not a general-purpose instruction-following upgrade.

Training

Base: meta-llama/Llama-3.1-8B-Instruct
Method: LoRA (r=16, alpha=32, dropout=0.05, target modules q/k/v/o_proj), full merge published here
Platform: Together AI managed fine-tuning
Dataset: 2,349 examples, protocol0_sft_v3 system prompt (https://github.com/soulinpsyabstract/sipa-os-governance/blob/main/AI_EXPERIMENTS/DATASETS/protocol0_sft_v3_full.jsonl)

Status

Trained and weights secured. Not yet behaviorally benchmarked against the base model — this repo documents both positive and negative/inconclusive results for every experiment in this series (see the AI_EXPERIMENTS folder above), and this model's write-up is pending. Do not treat this as a validated result until a corresponding EXP write-up is published.

Part of SIPA OS

Full experiment log: https://huggingface.co/datasets/SoulInPsyAbstract/sipa-os-governance
Related specialist adapter: https://huggingface.co/SoulInPsyAbstract/specialist-b-refusal-governance

License

Distributed under the Llama 3.1 Community License, per the base model's terms.

Downloads last month: 21

Safetensors

Model size

8B params

Tensor type

BF16

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for SoulInPsyAbstract/protocol0-llama-3.1-8b-v5

Base model

meta-llama/Llama-3.1-8B

Finetuned

meta-llama/Llama-3.1-8B-Instruct

Adapter

(2898)

this model

SoulInPsyAbstract
/

protocol0-llama-3.1-8b-v5

protocol0-llama-3.1-8b-v5

Training

Status

Part of SIPA OS

License

Model tree for SoulInPsyAbstract/protocol0-llama-3.1-8b-v5

Dataset used to train SoulInPsyAbstract/protocol0-llama-3.1-8b-v5