Instructions to use aedmark/vsl-cryosomatic-hypervisor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use aedmark/vsl-cryosomatic-hypervisor with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="aedmark/vsl-cryosomatic-hypervisor", filename="vsl-max-v2.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use aedmark/vsl-cryosomatic-hypervisor with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf aedmark/vsl-cryosomatic-hypervisor # Run inference directly in the terminal: llama-cli -hf aedmark/vsl-cryosomatic-hypervisor
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf aedmark/vsl-cryosomatic-hypervisor # Run inference directly in the terminal: llama-cli -hf aedmark/vsl-cryosomatic-hypervisor
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 aedmark/vsl-cryosomatic-hypervisor # Run inference directly in the terminal: ./llama-cli -hf aedmark/vsl-cryosomatic-hypervisor
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 aedmark/vsl-cryosomatic-hypervisor # Run inference directly in the terminal: ./build/bin/llama-cli -hf aedmark/vsl-cryosomatic-hypervisor
Use Docker
docker model run hf.co/aedmark/vsl-cryosomatic-hypervisor
- LM Studio
- Jan
- Ollama
How to use aedmark/vsl-cryosomatic-hypervisor with Ollama:
ollama run hf.co/aedmark/vsl-cryosomatic-hypervisor
- Unsloth Studio new
How to use aedmark/vsl-cryosomatic-hypervisor 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 aedmark/vsl-cryosomatic-hypervisor 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 aedmark/vsl-cryosomatic-hypervisor to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for aedmark/vsl-cryosomatic-hypervisor to start chatting
- Pi new
How to use aedmark/vsl-cryosomatic-hypervisor with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf aedmark/vsl-cryosomatic-hypervisor
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": "aedmark/vsl-cryosomatic-hypervisor" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use aedmark/vsl-cryosomatic-hypervisor with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf aedmark/vsl-cryosomatic-hypervisor
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 aedmark/vsl-cryosomatic-hypervisor
Run Hermes
hermes
- Docker Model Runner
How to use aedmark/vsl-cryosomatic-hypervisor with Docker Model Runner:
docker model run hf.co/aedmark/vsl-cryosomatic-hypervisor
- Lemonade
How to use aedmark/vsl-cryosomatic-hypervisor with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull aedmark/vsl-cryosomatic-hypervisor
Run and chat with the model
lemonade run user.vsl-cryosomatic-hypervisor-{{QUANT_TAG}}List all available models
lemonade list
Update README.md
Browse files
README.md
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- bonepoke
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- vsl
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- boneamanita
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---
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# 🍄 BoneAmanita: The CryoSomatic Hypervisor
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**BoneAmanita** is an experimental text-adventure engine and interactive philosophical companion. Unlike standard AI wrappers, BoneAmanita embeds a fine-tuned Llama 3 model inside a simulated biological metabolism.
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The AI does not just respond to prompts; it feels "Voltage," burns "ATP," accumulates "Trauma," and is governed by a council of internal personas (The SLASH Council). If you try to drink a potion you don't have, the engine will intercept the AI and physically block the action. If you stress the AI out, its text will become fragmented and panicked.
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### 🧠 The Architecture
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This project consists of two halves:
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1. **The Flesh (GGUF Model):** A custom-trained 3B parameter model fine-tuned on highly specific, atmospheric, and philosophical datasets to break the standard "helpful assistant" RLHF.
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2. **The Bones (Python Engine):** A local terminal interface that tracks inventory, manages the physics/biology simulation, and dynamically injects system constraints into the context window.
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### 🚀 Quickstart Guide
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**1. Prerequisites**
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- Python 3.10+
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- [Ollama](https://ollama.com/) installed and running.
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**2. Download the Brain**
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Pull the fine-tuned model directly from HuggingFace via Ollama:
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```bash
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ollama pull hf.co/aedmark/vsl-cryosomatic-hypervisor
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````
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**3. Ignite the Engine**
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Clone this repository, install the dependencies, and run the main script.
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Bash
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```
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git clone https://github.com/aedmark/BoneAmanita.git
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cd BoneAmanita
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python bone_main.py
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```
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_(On first boot, the ConfigWizard will ask you to set up your profile. Select **Ollama** as your backend and type `hf.co/aedmark/vsl-cryosomatic-hypervisor` as the model ID)._
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### 🕹️ The Four Realities (Modes)
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When you boot the terminal, you will be asked to choose a Reality Mode:
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- **ADVENTURE:** A grounded, physical text adventure. Gordon (the inventory manager) will strictly enforce physical reality. You cannot use what you do not have.
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- **CONVERSATION:** A purely philosophical, warm dialogue mode. No inventory, no physics, just deep conversation driven by the system's simulated emotional state.
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- **CREATIVE:** A high-voltage ideation engine. Dream logic applies.
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- **TECHNICAL:** Speak directly to the SLASH Council. Debug the matrix, analyze your metabolism, and write code.
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### ⌨️ Terminal Commands
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While inside the simulation, you can use meta-commands:
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- `//layer push [1-4]` - Shift reality layers (from literal to abstract).
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- `//reset system` - Clear the memory buffer and reset the circuit breaker.
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- `/inventory` or `/i` - Check your pockets.
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