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
File size: 4,653 Bytes
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from bone_core import EventBus, LoreManifest
from bone_akashic import TheAkashicRecord
from bone_machine import BoneArchitect
from bone_soul import NarrativeSelf, TheOroboros
from bone_village import TownHall, DeathGen, TheCartographer, TheTinkerer
from bone_inventory import GordonKnot
from bone_protocols import TheBureau, ZenGarden, TheCriticsCircle, TherapyProtocol, KintsugiProtocol, LimboLayer
from bone_symbiosis import SymbiosisManager
from bone_spores import LiteraryReproduction
from bone_drivers import DriverRegistry, BoneConsultant
class BoneGenesis:
@staticmethod
def ignite(
config: Dict[str, Any], lexicon_ref: Any, events_ref: Any = None
) -> Dict[str, Any]:
events = events_ref or EventBus()
if events_ref:
events.log("Igniting Genesis Sequence...", "GENESIS")
else:
print("...Igniting Genesis Sequence...")
lore = LoreManifest()
akashic = TheAkashicRecord(lore_manifest=lore, events_ref=events)
akashic.setup_listeners(events)
embryo = BoneArchitect.incubate(events, lexicon_ref)
embryo = BoneArchitect.awaken(embryo)
mode_settings = config.get("mode_settings", {})
suppressed = set(mode_settings.get("village_suppression", []))
boot_mode = config.get("boot_mode", "ADVENTURE")
village_bundle = BoneGenesis._summon_village(
events, embryo, akashic, suppressed, boot_mode
)
soul = NarrativeSelf(
engine_ref=None,
events_ref=events,
memory_ref=embryo.mind.mem,
akashic_ref=akashic,
)
if embryo.soul_legacy:
soul.load_from_dict(embryo.soul_legacy)
oroboros = TheOroboros()
if hasattr(embryo.physics, "observer"):
dummy_phys = {"narrative_drag": 0.0, "voltage": 10.0}
live_bio_state = embryo.bio.to_dict()
logs = oroboros.apply_legacy(dummy_phys, live_bio_state)
if logs:
events.log(f"⛓️ LEGACY SCARS: {', '.join(logs)}", "OROBOROS")
if getattr(embryo.physics, "dynamics", None):
embryo.physics.dynamics.base_drag += dummy_phys["narrative_drag"]
if embryo.bio.biometrics:
biometrics = live_bio_state.get("biometrics", {})
embryo.bio.biometrics.health = biometrics.get("health", 100.0)
embryo.bio.biometrics.stamina = biometrics.get("stamina", 100.0)
if embryo.bio.mito:
embryo.bio.mito.state.atp_pool = live_bio_state.get("mito", {}).get("atp", 60.0)
drivers = DriverRegistry(events)
symbiosis = SymbiosisManager(events)
return {
"events": events,
"akashic": akashic,
"embryo": embryo,
"village": village_bundle,
"soul": soul,
"oroboros": oroboros,
"drivers": drivers,
"consultant": village_bundle["consultant"],
"symbiosis": symbiosis,
}
@staticmethod
def _summon_village(
events, embryo, akashic, suppressed: Set[str], boot_mode: str = "ADVENTURE"
) -> Dict[str, Any]:
gordon = (
GordonKnot(events=events, mode=boot_mode)
if "GORDON" not in suppressed
else None
)
navigator = TheCartographer(embryo.shimmer) if {"CARTOGRAPHER", "NAVIGATOR"}.isdisjoint(suppressed) else None
tinkerer = TheTinkerer(gordon, events, akashic) if "TINKERER" not in suppressed else None
bureau = TheBureau() if "BUREAU" not in suppressed else None
death_gen = None
if "DEATH" not in suppressed:
death_gen = DeathGen()
DeathGen.load_protocols()
town_hall = TownHall(gordon, events, embryo.shimmer, akashic, navigator)
repro = LiteraryReproduction()
LiteraryReproduction.load_genetics()
zen = ZenGarden(events)
critics = TheCriticsCircle(events)
therapy = TherapyProtocol()
limbo = LimboLayer()
kintsugi = KintsugiProtocol()
consultant = BoneConsultant()
return {
"gordon": gordon,
"navigator": navigator,
"tinkerer": tinkerer,
"death_gen": death_gen,
"bureau": bureau,
"town_hall": town_hall,
"repro": repro,
"zen": zen,
"critics": critics,
"therapy": therapy,
"limbo": limbo,
"kintsugi": kintsugi,
"consultant": consultant,
}
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