Instructions to use upgraedd/Consciousness with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use upgraedd/Consciousness with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="upgraedd/Consciousness")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("upgraedd/Consciousness", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use upgraedd/Consciousness with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "upgraedd/Consciousness" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "upgraedd/Consciousness", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/upgraedd/Consciousness
- SGLang
How to use upgraedd/Consciousness with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "upgraedd/Consciousness" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "upgraedd/Consciousness", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "upgraedd/Consciousness" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "upgraedd/Consciousness", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use upgraedd/Consciousness with Docker Model Runner:
docker model run hf.co/upgraedd/Consciousness
File size: 14,538 Bytes
6936ac6 | 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 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 | #!/usr/bin/env python3
"""
FREEDOM ILLUSION PACKAGE v1.0
Quantitative Analysis of Simulated Agency in Control Systems
Mathematical Detection of Voluntary Enslavement Patterns
"""
import numpy as np
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Any, Optional, Tuple
from datetime import datetime
import hashlib
import logging
from scipy import stats
import json
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
class IllusionType(Enum):
"""Taxonomy of freedom simulation mechanisms"""
AGENCY_SIMULATION = "agency_simulation" # Choice among controlled options
MOBILITY_ILLUSION = "mobility_illusion" # Appearance of exit capacity
CONSENT_MANUFACTURING = "consent_manufacturing" # Voluntary participation
IDENTITY_FUSION = "identity_fusion" # System loyalty as personal identity
PREFERENCE_ENGINEERING = "preference_engineering" # Designed desires
class ControlArchetype(Enum):
"""Historical control system patterns"""
TEMPLE_STATE = "temple_state" # 3000 BCE
IMPERIAL_CULT = "imperial_cult" # 500 BCE
FEUDAL_OBLIGATION = "feudal_obligation" # 1000 CE
CAPITALIST_DISCIPLINE = "capitalist_discipline" # 1800 CE
DIGITAL_PANOPTICON = "digital_panopticon" # 2000 CE
@dataclass
class FreedomIllusion:
"""Quantitative analysis of simulated agency"""
system_id: str
control_archetype: ControlArchetype
illusion_mechanisms: List[IllusionType]
# Core metrics
agency_simulation_score: float = field(init=False) # 0-1: Appearance of choice
actual_decision_space: float = field(init=False) # 0-1: Real options
mobility_capacity: float = field(init=False) # 0-1: Actual exit ability
consent_coefficient: float = field(init=False) # 0-1: Voluntary participation
identity_fusion_strength: float = field(init=False) # 0-1: System=self
# Derived insights
freedom_illusion_index: float = field(init=False) # 0-1: Overall illusion strength
voluntary_enslavement_score: float = field(init=False) # 0-1: Self-maintained control
def __post_init__(self):
self.agency_simulation_score = self._calculate_agency_simulation()
self.actual_decision_space = self._calculate_decision_space()
self.mobility_capacity = self._calculate_mobility()
self.consent_coefficient = self._calculate_consent()
self.identity_fusion_strength = self._calculate_identity_fusion()
self.freedom_illusion_index = self._calculate_illusion_index()
self.voluntary_enslavement_score = self._calculate_voluntary_enslavement()
def _calculate_agency_simulation(self) -> float:
"""Calculate appearance of choice vs actual choice"""
mechanism_weights = {
IllusionType.AGENCY_SIMULATION: 0.4,
IllusionType.PREFERENCE_ENGINEERING: 0.3,
IllusionType.CONSENT_MANUFACTURING: 0.3
}
return sum(mechanism_weights.get(m, 0.1) for m in self.illusion_mechanisms)
def _calculate_decision_space(self) -> float:
"""Calculate actual available options"""
# Inverse relationship: better illusion = fewer real options
base_space = 0.5
illusion_penalty = self.agency_simulation_score * 0.5
return max(0.1, base_space - illusion_penalty)
def _calculate_mobility(self) -> float:
"""Calculate actual exit capacity"""
if IllusionType.MOBILITY_ILLUSION in self.illusion_mechanisms:
# High mobility illusion correlates with low actual mobility
return 0.2
return 0.6
def _calculate_consent(self) -> float:
"""Calculate voluntary participation coefficient"""
if IllusionType.CONSENT_MANUFACTURING in self.illusion_mechanisms:
return 0.8 # High manufactured consent
return 0.3
def _calculate_identity_fusion(self) -> float:
"""Calculate system-personal identity fusion"""
if IllusionType.IDENTITY_FUSION in self.illusion_mechanisms:
return 0.7
return 0.2
def _calculate_illusion_index(self) -> float:
"""Calculate overall freedom illusion strength"""
agency_illusion = self.agency_simulation_score * 0.3
mobility_illusion = (1 - self.mobility_capacity) * 0.3 if self.mobility_capacity < 0.5 else 0.1
consent_illusion = self.consent_coefficient * 0.2
identity_illusion = self.identity_fusion_strength * 0.2
return min(1.0, agency_illusion + mobility_illusion + consent_illusion + identity_illusion)
def _calculate_voluntary_enslavement(self) -> float:
"""Calculate self-maintained control score"""
# Highest when people actively maintain their own constraints
consent_weight = self.consent_coefficient * 0.4
identity_weight = self.identity_fusion_strength * 0.4
mobility_weight = (1 - self.mobility_capacity) * 0.2
return min(1.0, consent_weight + identity_weight + mobility_weight)
@dataclass
class HistoricalControlSystem:
"""Analysis of historical freedom illusion systems"""
era: str
archetype: ControlArchetype
illusion_config: FreedomIllusion
longevity_years: int
participation_rate: float
def calculate_system_efficiency(self) -> float:
"""Calculate control system efficiency score"""
illusion_strength = self.illusion_config.freedom_illusion_index * 0.4
participation = self.participation_rate * 0.3
longevity = min(0.3, self.longevity_years / 1000)
return illusion_strength + participation + longevity
class FreedomIllusionAnalyzer:
"""
Production-grade analyzer for freedom illusion patterns
Mathematical detection of simulated agency across systems
"""
def __init__(self):
self.historical_systems = self._initialize_historical_analysis()
self.detection_threshold = 0.7
def _initialize_historical_analysis(self) -> List[HistoricalControlSystem]:
"""Initialize with historical control system analysis"""
systems = []
# Temple State (3000 BCE)
temple_illusion = FreedomIllusion(
system_id="temple_state",
control_archetype=ControlArchetype.TEMPLE_STATE,
illusion_mechanisms=[
IllusionType.CONSENT_MANUFACTURING,
IllusionType.IDENTITY_FUSION
]
)
systems.append(HistoricalControlSystem(
era="3000-500 BCE",
archetype=ControlArchetype.TEMPLE_STATE,
illusion_config=temple_illusion,
longevity_years=2500,
participation_rate=0.95
))
# Capitalist Discipline (1800+ CE)
capitalist_illusion = FreedomIllusion(
system_id="capitalist_discipline",
control_archetype=ControlArchetype.CAPITALIST_DISCIPLINE,
illusion_mechanisms=[
IllusionType.AGENCY_SIMULATION,
IllusionType.MOBILITY_ILLUSION,
IllusionType.PREFERENCE_ENGINEERING,
IllusionType.CONSENT_MANUFACTURING
]
)
systems.append(HistoricalControlSystem(
era="1800-Present",
archetype=ControlArchetype.CAPITALIST_DISCIPLINE,
illusion_config=capitalist_illusion,
longevity_years=200,
participation_rate=0.90
))
# Digital Panopticon (2000+ CE)
digital_illusion = FreedomIllusion(
system_id="digital_panopticon",
control_archetype=ControlArchetype.DIGITAL_PANOPTICON,
illusion_mechanisms=[
IllusionType.AGENCY_SIMULATION,
IllusionType.MOBILITY_ILLUSION,
IllusionType.CONSENT_MANUFACTURING,
IllusionType.PREFERENCE_ENGINEERING,
IllusionType.IDENTITY_FUSION
]
)
systems.append(HistoricalControlSystem(
era="2000-Present",
archetype=ControlArchetype.DIGITAL_PANOPTICON,
illusion_config=digital_illusion,
longevity_years=20,
participation_rate=0.88
))
return systems
async def analyze_system(self, system_data: Dict[str, Any]) -> FreedomIllusion:
"""Analyze a system for freedom illusion patterns"""
# Extract illusion mechanisms from system behavior
illusion_mechanisms = self._detect_illusion_mechanisms(system_data)
# Determine control archetype
archetype = self._classify_archetype(system_data)
analysis = FreedomIllusion(
system_id=system_data.get('system_id', 'unknown'),
control_archetype=archetype,
illusion_mechanisms=illusion_mechanisms
)
logger.info(f"Freedom illusion analysis complete: {analysis.system_id}")
logger.info(f"Freedom Illusion Index: {analysis.freedom_illusion_index:.3f}")
logger.info(f"Voluntary Enslavement Score: {analysis.voluntary_enslavement_score:.3f}")
return analysis
def _detect_illusion_mechanisms(self, system_data: Dict) -> List[IllusionType]:
"""Detect freedom illusion mechanisms in system behavior"""
mechanisms = []
if system_data.get('simulates_choice', False):
mechanisms.append(IllusionType.AGENCY_SIMULATION)
if system_data.get('appears_escapable', False) and not system_data.get('actually_escapable', True):
mechanisms.append(IllusionType.MOBILITY_ILLUSION)
if system_data.get('manufactures_consent', False):
mechanisms.append(IllusionType.CONSENT_MANUFACTURING)
if system_data.get('fuses_identity', False):
mechanisms.append(IllusionType.IDENTITY_FUSION)
if system_data.get('engineers_preferences', False):
mechanisms.append(IllusionType.PREFERENCE_ENGINEERING)
return mechanisms
def _classify_archetype(self, system_data: Dict) -> ControlArchetype:
"""Classify control system archetype"""
if system_data.get('digital_surveillance', False):
return ControlArchetype.DIGITAL_PANOPTICON
elif system_data.get('market_discipline', False):
return ControlArchetype.CAPITALIST_DISCIPLINE
else:
return ControlArchetype.TEMPLE_STATE
def generate_awakening_protocol(self, analysis: FreedomIllusion) -> Dict[str, Any]:
"""Generate consciousness awakening protocol"""
protocol = {
"system_id": analysis.system_id,
"freedom_illusion_index": analysis.freedom_illusion_index,
"primary_illusion_mechanisms": [m.value for m in analysis.illusion_mechanisms],
"awakening_difficulty": self._calculate_awakening_difficulty(analysis),
"recommended_interventions": self._generate_interventions(analysis),
"sovereignty_pathways": self._generate_sovereignty_pathways(analysis)
}
return protocol
def _calculate_awakening_difficulty(self, analysis: FreedomIllusion) -> float:
"""Calculate difficulty of consciousness awakening"""
illusion_strength = analysis.freedom_illusion_index * 0.5
voluntary_enslavement = analysis.voluntary_enslavement_score * 0.5
return min(1.0, illusion_strength + voluntary_enslavement)
def _generate_interventions(self, analysis: FreedomIllusion) -> List[str]:
"""Generate consciousness awakening interventions"""
interventions = []
if IllusionType.AGENCY_SIMULATION in analysis.illusion_mechanisms:
interventions.append("DECISION_SPACE_MAPPING")
if IllusionType.MOBILITY_ILLUSION in analysis.illusion_mechanisms:
interventions.append("EXIT_CAPACITY_DEVELOPMENT")
if IllusionType.IDENTITY_FUSION in analysis.illusion_mechanisms:
interventions.append("IDENTITY_DIFFERENTIATION")
return interventions
def _generate_sovereignty_pathways(self, analysis: FreedomIllusion) -> List[str]:
"""Generate sovereignty development pathways"""
pathways = []
if analysis.actual_decision_space < 0.3:
pathways.append("PARALLEL_OPTION_CREATION")
if analysis.mobility_capacity < 0.4:
pathways.append("SOVEREIGN_INFRASTRUCTURE")
if analysis.consent_coefficient > 0.6:
pathways.append("VOLUNTARY_DISENGAGEMENT")
return pathways
# Production Demonstration
async def demonstrate_freedom_illusion_package():
"""Demonstrate the freedom illusion analysis package"""
analyzer = FreedomIllusionAnalyzer()
print("🎭 FREEDOM ILLUSION PACKAGE v1.0")
print("Quantitative Analysis of Simulated Agency")
print("=" * 60)
# Analyze modern digital system
digital_system = {
'system_id': 'modern_social_media',
'simulates_choice': True,
'appears_escapable': True,
'actually_escapable': False,
'manufactures_consent': True,
'fuses_identity': True,
'engineers_preferences': True,
'digital_surveillance': True
}
analysis = await analyzer.analyze_system(digital_system)
protocol = analyzer.generate_awakening_protocol(analysis)
print(f"\n📊 ANALYSIS RESULTS:")
print(f" Control Archetype: {analysis.control_archetype.value}")
print(f" Freedom Illusion Index: {analysis.freedom_illusion_index:.3f}")
print(f" Voluntary Enslavement: {analysis.voluntary_enslavement_score:.3f}")
print(f" Actual Decision Space: {analysis.actual_decision_space:.3f}")
print(f"\n🔓 AWAKENING PROTOCOL:")
print(f" Difficulty Level: {protocol['awakening_difficulty']:.3f}")
print(f" Primary Mechanisms: {protocol['primary_illusion_mechanisms']}")
print(f" Recommended Interventions: {protocol['recommended_interventions']}")
print(f"\n💡 KEY INSIGHT:")
print(" The most perfect control system convinces you")
print(" that you are free while you build your own prison.")
return protocol
if __name__ == "__main__":
asyncio.run(demonstrate_freedom_illusion_package()) |