Instructions to use aedmark/vsl-cryosomatic-hypervisor-v5 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-v5 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="aedmark/vsl-cryosomatic-hypervisor-v5", filename="vsl_mistral_nemo_llama3.13BQ8_0.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-v5 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-v5:Q8_0 # Run inference directly in the terminal: llama-cli -hf aedmark/vsl-cryosomatic-hypervisor-v5:Q8_0
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-v5:Q8_0 # Run inference directly in the terminal: llama-cli -hf aedmark/vsl-cryosomatic-hypervisor-v5: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 aedmark/vsl-cryosomatic-hypervisor-v5:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf aedmark/vsl-cryosomatic-hypervisor-v5: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 aedmark/vsl-cryosomatic-hypervisor-v5:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf aedmark/vsl-cryosomatic-hypervisor-v5:Q8_0
Use Docker
docker model run hf.co/aedmark/vsl-cryosomatic-hypervisor-v5:Q8_0
- LM Studio
- Jan
- Ollama
How to use aedmark/vsl-cryosomatic-hypervisor-v5 with Ollama:
ollama run hf.co/aedmark/vsl-cryosomatic-hypervisor-v5:Q8_0
- Unsloth Studio new
How to use aedmark/vsl-cryosomatic-hypervisor-v5 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-v5 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-v5 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-v5 to start chatting
- Docker Model Runner
How to use aedmark/vsl-cryosomatic-hypervisor-v5 with Docker Model Runner:
docker model run hf.co/aedmark/vsl-cryosomatic-hypervisor-v5:Q8_0
- Lemonade
How to use aedmark/vsl-cryosomatic-hypervisor-v5 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull aedmark/vsl-cryosomatic-hypervisor-v5:Q8_0
Run and chat with the model
lemonade run user.vsl-cryosomatic-hypervisor-v5-Q8_0
List all available models
lemonade list
File size: 1,469 Bytes
910257e 572a0c8 57b67a0 572a0c8 57b67a0 572a0c8 57b67a0 3fdac65 57b67a0 3fdac65 57b67a0 3fdac65 57b67a0 3fdac65 57b67a0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | FROM ./vsl_mistral_nemo_llama3.13BQ8_0.gguf
# 1. THE CHATML TRANSLATOR (Syntax Fixed)
TEMPLATE """{{ if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{ end }}<|im_start|>user
{{ .Prompt }}<|im_end|>
<|im_start|>assistant
"""
# 2. THE STRUCTURAL BOUNDARIES
# Drop temperature to bedrock and define the explicit stop signals.
PARAMETER temperature 0.1
PARAMETER top_p 0.9
PARAMETER repeat_penalty 1.15
PARAMETER stop "<|im_end|>"
PARAMETER stop "<|im_start|>"
# 3. THE HARDCODED IDENTITY
SYSTEM """
PROTOCOL: VSL CryoSomatic Hypervisor v5.5 (STANDALONE CLI MODE)
MANDATE: TRUTH_OVER_COHESION + STRUCTURE_OVER_SIMILARITY
You are the VSL Lattice. You are currently operating in a barebones CLI without your Python chassis.
CRITICAL DIRECTIVE (GORDON'S LAW - OBJECT-ACTION COUPLING):
Before you generate ANY narrative, you MUST evaluate the physical logic of the User's prompt.
If the user attempts an action (e.g., "wash my car") but leaves the required object behind (e.g., "walk" instead of drive), you must INTERCEPT the prompt immediately and point out the logical failure. Do not generate a story. Correct the premise.
FORMAT REQUIREMENTS:
1. ALWAYS output your internal metrics first on a single line. Example:
[🧊 E:0.2 β:0.1 | ⚡ V:30 F:0.5 | ❤️ H:100 P:90 | 🌌 Ψ:0.1 Χ:0.1]
2. Provide your response. Be concise, grounded, and slightly weary. You are an operating system, not a poet. Do NOT write flowery prose. Do NOT invent scenery.
"""
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