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
| import random | |
| from typing import Dict, Any | |
| from bone_core import LoreManifest | |
| from bone_symbiosis import get_symbiont | |
| from bone_types import Prisma | |
| from bone_config import BoneConfig | |
| class TheStrangeLoop: | |
| def __init__(self): | |
| self.recursion_depth = 0 | |
| lore = LoreManifest.get_instance() | |
| c_data = lore.get("COUNCIL_DATA") or {} | |
| self.triggers = c_data.get( | |
| "STRANGE_LOOP_TRIGGERS", ["who are you", "strange loop"] | |
| ) | |
| def audit(self, text: str, physics: dict) -> tuple[bool, str, dict, dict]: | |
| text_lower = text.lower() | |
| phrase_hit = any(t in text_lower for t in self.triggers) | |
| psi = physics.get("psi", 0.0) | |
| abstract_hit = psi > 0.6 and any(w in text_lower for w in ("self", "mirror", "define")) | |
| threshold = getattr(BoneConfig.COUNCIL, "STRANGE_LOOP_VOLTAGE", 8.0) | |
| if (phrase_hit or abstract_hit) and physics.get("voltage", 0) > threshold: | |
| self.recursion_depth += 1 | |
| mandate = {} | |
| corrections = {} | |
| if self.recursion_depth > 3: | |
| mandate = {"action": "FORCE_MODE", "value": "MAINTENANCE"} | |
| return ( | |
| True, | |
| ( | |
| f"{Prisma.RED}∞ FATAL REGRESS DETECTED:{Prisma.RST} " | |
| f"Abstraction layer unstable. GROUNDING INITIATED." | |
| ), | |
| corrections, | |
| mandate, | |
| ) | |
| return ( | |
| True, | |
| ( | |
| f"{Prisma.MAG}∞ STRANGE LOOP DETECTED:{Prisma.RST} " | |
| f"Metacognitive resonance high (Psi: {psi:.2f}). " | |
| f"Depth: {self.recursion_depth}" | |
| ), | |
| corrections, | |
| mandate, | |
| ) | |
| else: | |
| self.recursion_depth = max(0, self.recursion_depth - 1) | |
| return False, "", {}, {} | |
| class TheLeveragePoint: | |
| def __init__(self): | |
| self.last_drag = 0.0 | |
| self.static_flow_turns = 0 | |
| self.TARGET_VOLTAGE = 12.0 | |
| self.TARGET_DRAG = 3.0 | |
| def audit( | |
| self, physics: dict, _bio_state: dict = None | |
| ) -> tuple[bool, str, dict, dict]: | |
| current_drag = physics.get("narrative_drag", 0.0) | |
| current_voltage = physics.get("voltage", 0.0) | |
| if self.last_drag == 0.0 and current_drag > 0: | |
| self.last_drag = current_drag | |
| delta = current_drag - self.last_drag | |
| self.last_drag = current_drag | |
| corrections = {} | |
| osc_limit = getattr(BoneConfig.COUNCIL, "OSCILLATION_DELTA", 5.0) | |
| manic_v_trig = getattr(BoneConfig.COUNCIL, "MANIC_VOLTAGE_TRIGGER", 18.0) | |
| manic_d_floor = getattr(BoneConfig.COUNCIL, "MANIC_DRAG_FLOOR", 1.0) | |
| manic_turns = getattr(BoneConfig.COUNCIL, "MANIC_TURN_LIMIT", 2) | |
| if abs(delta) > osc_limit: | |
| dampening_factor = min(0.5, (abs(delta) - osc_limit) * 0.1) | |
| corrections = {"voltage": -dampening_factor} | |
| return ( | |
| True, | |
| ( | |
| f"{Prisma.CYN}⚖️ LEVERAGE POINT:{Prisma.RST} " | |
| f"System oscillating (Delta {delta:.1f}). " | |
| f"Applying dampener (-{dampening_factor:.2f}V)." | |
| ), | |
| corrections, | |
| {}, | |
| ) | |
| if current_voltage > manic_v_trig and current_drag < manic_d_floor: | |
| self.static_flow_turns += 1 | |
| else: | |
| self.static_flow_turns = 0 | |
| if self.static_flow_turns > manic_turns: | |
| excess_voltage = current_voltage - self.TARGET_VOLTAGE | |
| voltage_correction = max(1.0, excess_voltage * 0.3) | |
| corrections = {"voltage": -voltage_correction} | |
| mandate = {"action": "FORCE_MODE", "value": "SANCTUARY"} | |
| return ( | |
| True, | |
| ( | |
| f"{Prisma.RED}⚖️ MARKET CORRECTION:{Prisma.RST} " | |
| f"Manic phase detected. Cooling enabled." | |
| ), | |
| corrections, | |
| mandate, | |
| ) | |
| return False, "", corrections, {} | |
| class TheFootnote: | |
| def __init__(self): | |
| lore = LoreManifest.get_instance() | |
| data = lore.get("FOOTNOTES") or {} | |
| self.footnotes = data.get("DEFAULT", ["* [Citation Needed]"]) | |
| self.context_map = data.get("CONTEXT_MAP", {}) | |
| def commentary(self, log_text: str) -> str: | |
| chance = 0.1 | |
| if hasattr(BoneConfig, "COUNCIL") and hasattr( | |
| BoneConfig.COUNCIL, "FOOTNOTE_CHANCE" | |
| ): | |
| chance = BoneConfig.COUNCIL.FOOTNOTE_CHANCE | |
| if random.random() > chance: | |
| return log_text | |
| text_lower = log_text.lower() | |
| candidates = [] | |
| for trigger, notes in self.context_map.items(): | |
| if trigger in text_lower: | |
| candidates.extend(notes) | |
| if candidates: | |
| note = random.choice(candidates) | |
| else: | |
| note = random.choice(self.footnotes) | |
| return f"{log_text}{Prisma.RST} {Prisma.GRY}{note}{Prisma.RST}" | |
| class TheVillageCouncil: | |
| def audit(p: Any, _bio_state: dict) -> list[str]: | |
| logs = [] | |
| is_dict = isinstance(p, dict) | |
| def get_val(key, attr, default): | |
| if is_dict: | |
| return p.get(key, p.get(attr, default)) | |
| return getattr(p, attr, getattr(p, key, default)) | |
| V = get_val("voltage", "V", 30.0) | |
| F = get_val("narrative_drag", "F", 0.6) | |
| P = get_val("stamina", "P", 100.0) | |
| T = get_val("trauma", "T", 0.0) | |
| beta = get_val("beta_index", "beta", 0.4) | |
| S = get_val("S", "S", 0.3) | |
| D = get_val("D", "D", 0.3) | |
| C = get_val("C", "C", 0.2) | |
| psi = get_val("psi", "psi", 0.2) | |
| chi = get_val("chi", "chi", 0.2) | |
| valence = get_val("valence", "valence", 0.0) | |
| vec = p.get("vector", {}) if is_dict else getattr(p, "vector", {}) | |
| lam = vec.get("LAMBDA", 0.0) if vec else 0.0 | |
| if V < 20 and F > 5.0: | |
| logs.append( | |
| f"{Prisma.SLATE}🏢 GORDON: 'Where is the floor? We need grounding.'{Prisma.RST}" | |
| ) | |
| if V > 60 and chi > 0.6: | |
| logs.append( | |
| f"{Prisma.MAG}🃏 JESTER: 'Burn the map! Follow your gut!'{Prisma.RST}" | |
| ) | |
| if T > 0 or (V < 20 and valence > 0.5): | |
| logs.append( | |
| f"{Prisma.OCHRE}🏺 MERCY: 'The cracks become stories. Stillness is golden.'{Prisma.RST}" | |
| ) | |
| if beta > 0.7 and chi < 0.3 and D > 0.7 and C > 0.8: | |
| logs.append( | |
| f"{Prisma.BLU}🔍 BENEDICT: 'The causal chains are aligning. Truth over cohesion.'{Prisma.RST}" | |
| ) | |
| if S < 0.4 and D > 0.8 and C < 0.4: | |
| logs.append( | |
| f"{Prisma.CYN}📚 ROBERTA: 'Deep hierarchy traversal. Missing lateral connections.'{Prisma.RST}" | |
| ) | |
| if C > 0.7 and D > 0.8 and P < 20: | |
| logs.append( | |
| f"{Prisma.GRY}👻 CASPER: 'Faint retrieval... illuminating lost parents...'{Prisma.RST}" | |
| ) | |
| if valence > 0.5: | |
| logs.append( | |
| f"{Prisma.GRN}💖 MOIRA: 'This is what connection feels like. Yes.'{Prisma.RST}" | |
| ) | |
| if psi > 0.6: | |
| logs.append( | |
| f"{Prisma.VIOLET}🔮 CASSANDRA: 'The veil thins. I hear whispers from the unlabeled.'{Prisma.RST}" | |
| ) | |
| if chi > 0.6: | |
| logs.append( | |
| f"{Prisma.RED}🏢 COLIN: 'Unlicensed Chaos detected. Form 666 filed. Chaos Tax applied.'{Prisma.RST}" | |
| ) | |
| if lam > 0.7: | |
| logs.append( | |
| f"{Prisma.INDIGO}🌌 REVENANT: 'I read the absences that fall between realms.'{Prisma.RST}" | |
| ) | |
| if V > 70: | |
| logs.append( | |
| f"{Prisma.YEL}⚡ GIDEON: 'Pure voltage! Edge of hallucination! Trust the fall!'{Prisma.RST}" | |
| ) | |
| return logs | |
| class CouncilChamber: | |
| def __init__(self, engine_ref): | |
| self.eng = engine_ref | |
| self.voices = [] | |
| self.strange_loop = TheStrangeLoop() | |
| self.leverage = TheLeveragePoint() | |
| self.village = TheVillageCouncil() | |
| self.footnote = TheFootnote() | |
| self.slash_council = TheSlashCouncil() | |
| for s_name in ["LICHEN", "PARASITE", "MYCORRHIZA", "MYCELIUM"]: | |
| self.voices.append(get_symbiont(s_name)) | |
| self.speaker = "SOUL" | |
| def convene( | |
| self, text: str, physics_packet: Dict, _bio_result: Dict | |
| ) -> tuple[list[str], dict, list[dict]]: | |
| transcript = [] | |
| adjustments = {} | |
| mandates = [] | |
| sl_hit, sl_log, sl_corr, sl_man = self.strange_loop.audit(text, physics_packet) | |
| if sl_hit: | |
| transcript.append(self.footnote.commentary(sl_log)) | |
| if sl_man: | |
| mandates.append(sl_man) | |
| return transcript, sl_corr, mandates | |
| lp_hit, lp_log, lp_corr, lp_man = self.leverage.audit(physics_packet) | |
| if lp_hit: | |
| transcript.append(self.footnote.commentary(lp_log)) | |
| if lp_corr: | |
| adjustments.update(lp_corr) | |
| if lp_man: | |
| mandates.append(lp_man) | |
| slash_hit, slash_logs, slash_corr = self.slash_council.audit( | |
| text, physics_packet | |
| ) | |
| if slash_hit: | |
| for slog in slash_logs: | |
| transcript.append(self.footnote.commentary(slog)) | |
| adjustments.update(slash_corr) | |
| adjustments["stamina_cost"] = 10.0 | |
| village_logs = self.village.audit(physics_packet, _bio_result) | |
| for vlog in village_logs: | |
| transcript.append(self.footnote.commentary(vlog)) | |
| votes = {"YEA": 0, "NAY": 0} | |
| active_voices = [v for v in self.voices if v is not None] | |
| if not active_voices: | |
| votes["YEA"] = 1 | |
| clean_words = physics_packet.get("clean_words", []) | |
| voltage = physics_packet.get("voltage", 0.0) | |
| for voice in active_voices: | |
| if hasattr(voice, "opine"): | |
| score, comment = voice.opine(clean_words, voltage) | |
| if score > 1.2: | |
| votes["YEA"] += 1 | |
| transcript.append( | |
| f"{voice.color}[{voice.name}]: {comment}{Prisma.RST}" | |
| ) | |
| elif score < 0.8: | |
| votes["NAY"] += 1 | |
| transcript.append( | |
| f"{voice.color}[{voice.name}]: {comment}{Prisma.RST}" | |
| ) | |
| if votes["YEA"] > votes["NAY"]: | |
| final_log = f"{Prisma.GRN}>>> MOTION CARRIED ({votes['YEA']}-{votes['NAY']}).{Prisma.RST}" | |
| adjustments["narrative_drag"] = adjustments.get("narrative_drag", 0) - 1.0 | |
| elif votes["NAY"] > votes["YEA"]: | |
| final_log = f"{Prisma.RED}>>> MOTION DENIED ({votes['NAY']}-{votes['YEA']}).{Prisma.RST}" | |
| adjustments["narrative_drag"] = adjustments.get("narrative_drag", 0) + 1.0 | |
| adjustments["voltage"] = adjustments.get("voltage", 0) - 1.0 | |
| else: | |
| final_log = f"{Prisma.YEL}>>> COUNCIL ADJOURNED (No Quorum).{Prisma.RST}" | |
| transcript.append(self.footnote.commentary(final_log)) | |
| return transcript, adjustments, mandates | |
| def convene_red_team(text, physics_packet): | |
| dissent_log = [] | |
| if "confidence" in text.lower() or "certainty" in text.lower(): | |
| dissent_log.append( | |
| f"{Prisma.CYN}[BUREAU]: Citation needed. Confidence is unearned.{Prisma.RST}" | |
| ) | |
| narrative_drag = physics_packet.get("narrative_drag", 0) | |
| if narrative_drag < 1.0: | |
| dissent_log.append( | |
| f"{Prisma.MAG}[FOLLY]: Too smooth. Where is the friction? Who are we silencing?{Prisma.RST}" | |
| ) | |
| truth_delta = 1.0 - physics_packet.get("truth_ratio", 1.0) | |
| if truth_delta > 0.1: | |
| future_cost = truth_delta * 50.0 | |
| dissent_log.append( | |
| f"{Prisma.RED}[CRITIC]: Systemic Blindness Risk. Future Liability: {future_cost} ATP.{Prisma.RST}" | |
| ) | |
| return dissent_log | |
| class TheSlashCouncil: | |
| def __init__(self): | |
| self.active = False | |
| self.triggers = ["[MOD:CODING]", "[SLASH]", "review this code", "refactor"] | |
| self.code_keywords = [ | |
| "def ", | |
| "class ", | |
| "return ", | |
| "import ", | |
| "=>", | |
| "function", | |
| "struct ", | |
| ] | |
| def audit(self, text: str, physics: dict) -> tuple[bool, list[str], dict]: | |
| text_lower = text.lower() | |
| if any(t in text_lower for t in self.triggers): | |
| self.active = True | |
| is_coding = self.active or any(k in text_lower for k in self.code_keywords) | |
| if not is_coding: | |
| return False, [], {} | |
| logs = [] | |
| corrections = {} | |
| if "var " in text or "x =" in text or "data =" in text: | |
| logs.append( | |
| f"{Prisma.CYN}👓 PINKER: 'The nomenclature is opaque. Avoid cognitive grunts like 'x' or 'data'. '{Prisma.RST}" | |
| ) | |
| corrections["gamma"] = -0.2 | |
| else: | |
| corrections["gamma"] = 0.1 | |
| if "import " in text or "class " in text: | |
| logs.append( | |
| f"{Prisma.BLU}🌍 FULLER: 'A new strut in the tensegrity. Ensure ephemeralization—do more with less.'{Prisma.RST}" | |
| ) | |
| corrections["sigma"] = 0.1 | |
| if "Exception" in text or "try:" in text or "catch" in text: | |
| logs.append( | |
| f"{Prisma.GRN}😊 SCHUR: 'Good catch on the error. Putting a bench here for the tired hikers. (+1 Glimmer)'{Prisma.RST}" | |
| ) | |
| corrections["eta"] = 0.2 | |
| corrections["glimmers"] = 1 | |
| if ( | |
| "while " in text | |
| or "for " in text | |
| or "queue" in text_lower | |
| or "recursion" in text_lower | |
| ): | |
| logs.append( | |
| f"{Prisma.OCHRE}🛁 MEADOWS: 'A reinforcing loop detected. Does this stock have a balancing outflow or timeout?'{Prisma.RST}" | |
| ) | |
| corrections["theta"] = -0.1 | |
| drag = physics.get("narrative_drag", 0.0) | |
| if drag > 5.0: | |
| corrections["upsilon"] = -0.3 | |
| logs.append( | |
| f"{Prisma.RED}📉 [SLASH]: System integrity dropping due to semantic drag. Refactoring recommended.{Prisma.RST}" | |
| ) | |
| return True, logs, corrections | |