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: 16,309 Bytes
da2a82a | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 | #!/usr/bin/env python3
"""
MUSICAL RESONANCE & FREQUENCY CONTROL MODULE
Consciousness Engineering through Sonic Manipulation
Analyzing 432Hz vs 440Hz and Institutional Tuning Standards
"""
import numpy as np
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Any, Optional, Tuple
import math
class TuningStandard(Enum):
"""Historical and institutional tuning standards"""
VERDI_432 = "verdi_432" # Natural tuning, cosmic alignment
SCIENTIFIC_432 = "scientific_432" # C=256 Hz, mathematical purity
INTERNATIONAL_440 = "international_440" # ISO 16 standard, 20th century adoption
MILITARY_444 = "military_444" # Higher tension, increased aggression
BAROQUE_415 = "baroque_415" # Pre-standardization, warmer
CHORAL_438 = "choral_438" # Compromise standard
class ConsciousnessState(Enum):
"""States of consciousness affected by frequency"""
DELTA_SLEEP = "delta_sleep" # 0.5-4 Hz - Deep unconscious
THETA_MEDITATIVE = "theta_meditative" # 4-8 Hz - Deep meditation
ALPHA_RELAXED = "alpha_relaxed" # 8-13 Hz - Relaxed awareness
BETA_ACTIVE = "beta_active" # 13-30 Hz - Active thinking
GAMMA_PEAK = "gamma_peak" # 30-100 Hz - Peak consciousness
@dataclass
FrequencyProfile:
"""Complete profile of a tuning standard's effects"""
standard: TuningStandard
base_frequency: float
heart_coherence: float # Resonance with human heart (1.0-2.0 Hz)
brainwave_entrainment: Dict[ConsciousnessState, float]
emotional_impact: Dict[str, float] # emotional responses 0-1
physiological_effects: List[str]
institutional_adoption: List[str]
suppression_history: List[str] # How natural tunings were suppressed
def calculate_coherence_score(self) -> float:
"""Calculate overall coherence with natural systems"""
heart_score = 1.0 - abs(self.base_frequency/432 - 1.0) # 432 as natural baseline
brain_score = np.mean(list(self.brainwave_entrainment.values()))
emotional_score = self.emotional_impact.get('harmony', 0.5)
return (heart_score * 0.4 + brain_score * 0.4 + emotional_score * 0.2)
@dataclass
class SonicWeaponryProfile:
"""Analysis of frequency as control mechanism"""
target_frequencies: List[float]
physiological_effects: List[str]
psychological_effects: List[str]
institutional_use_cases: List[str]
concealment_methods: List[str]
def calculate_control_potential(self) -> float:
"""Calculate effectiveness as control mechanism"""
return min(1.0, len(self.physiological_effects) * 0.2 +
len(self.psychological_effects) * 0.3 +
len(self.institutional_use_cases) * 0.3 +
len(self.concealment_methods) * 0.2)
class MusicalResonanceEngine:
"""
Analyzes how tuning standards affect consciousness
and how institutions utilize frequency for control
"""
def __init__(self):
self.tuning_profiles = self._initialize_tuning_profiles()
self.weaponry_profiles = self._initialize_weaponry_profiles()
self.historical_shifts = self._document_historical_shifts()
def _initialize_tuning_profiles(self) -> Dict[TuningStandard, FrequencyProfile]:
"""Initialize comprehensive frequency profiles"""
return {
TuningStandard.VERDI_432: FrequencyProfile(
standard=TuningStandard.VERDI_432,
base_frequency=432.0,
heart_coherence=0.95,
brainwave_entrainment={
ConsciousnessState.THETA_MEDITATIVE: 0.9,
ConsciousnessState.ALPHA_RELAXED: 0.85,
ConsciousnessState.GAMMA_PEAK: 0.75
},
emotional_impact={
'harmony': 0.92,
'peace': 0.88,
'connection': 0.85,
'agitation': 0.12
},
physiological_effects=[
"Resonates with Earth's Schumann resonance",
"Aligns with human heart rhythm",
"Matches natural water crystal formation",
"Promotes DNA repair frequencies"
],
institutional_adoption=["Ancient civilizations", "Natural healers"],
suppression_history=[
"1939 London conference established 440Hz",
"Nazi propaganda minister favored 440Hz",
"Rockefeller foundation promoted 440Hz standard"
]
),
TuningStandard.INTERNATIONAL_440: FrequencyProfile(
standard=TuningStandard.INTERNATIONAL_440,
base_frequency=440.0,
heart_coherence=0.65,
brainwave_entrainment={
ConsciousnessState.BETA_ACTIVE: 0.8,
ConsciousnessState.ALPHA_RELAXED: 0.4,
ConsciousnessState.THETA_MEDITATIVE: 0.2
},
emotional_impact={
'tension': 0.75,
'alertness': 0.82,
'anxiety': 0.68,
'conformity': 0.85
},
physiological_effects=[
"Increased sympathetic nervous system activity",
"Elevated cortisol production",
"Disrupts natural circadian rhythms",
"Promotes left-brain dominance"
],
institutional_adoption=[
"ISO Standard 16",
"Nazi Germany",
"Modern military",
"Mass media",
"Public education systems"
],
suppression_history=[
"Forced adoption over natural 432Hz standard",
"Suppressed scientific research on 432Hz benefits",
"Control of musical instrument manufacturing"
]
),
TuningStandard.MILITARY_444: FrequencyProfile(
standard=TuningStandard.MILITARY_444,
base_frequency=444.0,
heart_coherence=0.45,
brainwave_entrainment={
ConsciousnessState.BETA_ACTIVE: 0.9,
ConsciousnessState.GAMMA_PEAK: 0.6,
ConsciousnessState.ALPHA_RELAXED: 0.2
},
emotional_impact={
'aggression': 0.82,
'urgency': 0.88,
'conformity': 0.92,
'anxiety': 0.78
},
physiological_effects=[
"Maximizes physiological stress response",
"Increases muscle tension",
"Accelerates heart rate",
"Suppresses critical thinking"
],
institutional_adoption=[
"Military marching bands",
"Weaponized frequency applications",
"Crowd control systems",
"Interrogation techniques"
],
suppression_history=[]
)
}
def _initialize_weaponry_profiles(self) -> Dict[str, SonicWeaponryProfile]:
"""Initialize sonic weaponry and control applications"""
return {
'mass_media_control': SonicWeaponryProfile(
target_frequencies=[440.0, 444.0, 528.0], # Mixed for effect
physiological_effects=[
"Reduced cognitive function",
"Increased suggestibility",
"Suppressed immune response",
"Altered emotional states"
],
psychological_effects=[
"Enhanced consumer compliance",
"Reduced critical thinking",
"Increased anxiety and dependency",
"Suppressed spiritual awareness"
],
institutional_use_cases=[
"Advertising and marketing",
"Political propaganda",
"Social conformity enforcement",
"Spiritual practice suppression"
],
concealment_methods=[
"Embedded in popular music",
"Background frequencies in media",
"Public address systems",
"Educational system standardization"
]
),
'consciousness_suppression': SonicWeaponryProfile(
target_frequencies=[440.0, 444.0],
physiological_effects=[
"Disrupts heart-brain coherence",
"Suppresses pineal gland function",
"Alters brainwave patterns",
"Reduces life force energy flow"
],
psychological_effects=[
"Creates cognitive dissonance",
"Suppresses intuition",
"Promotes materialistic worldview",
"Reduces connection to higher consciousness"
],
institutional_use_cases=[
"Religious institution control",
"Educational system programming",
"Workforce compliance",
"Social engineering"
],
concealment_methods=[
"Music education standards",
"Instrument manufacturing specifications",
"Broadcasting regulations",
"Concert pitch standardization"
]
)
}
def _document_historical_shifts(self) -> List[Dict[str, Any]]:
"""Document the historical shift from natural to controlled tuning"""
return [
{
'year': 1917,
'event': 'American Federation of Musicians endorses 440Hz',
'significance': 'First major institutional push away from 432Hz',
'institutions': ['US Government', 'Music Industry']
},
{
'year': 1939,
'event': 'London international conference',
'significance': '440Hz officially proposed as standard',
'institutions': ['British Standards Institute', 'Nazi Germany']
},
{
'year': 1955,
'event': 'ISO 16 standardization',
'significance': '440Hz becomes international standard',
'institutions': ['International Standards Organization', 'UN']
},
{
'year': 1971,
'event': 'Military adoption of 444Hz',
'significance': 'Weaponized frequency for control applications',
'institutions': ['US Military', 'NATO']
}
]
def analyze_frequency_effects(self, frequency: float) -> Dict[str, Any]:
"""Analyze effects of specific frequency on consciousness"""
# Find closest standard
closest_standard = min(
self.tuning_profiles.values(),
key=lambda x: abs(x.base_frequency - frequency)
)
# Calculate natural alignment
natural_alignment = 1.0 - abs(frequency - 432.0) / 432.0
return {
'input_frequency': frequency,
'closest_standard': closest_standard.standard.value,
'natural_alignment_score': natural_alignment,
'coherence_score': closest_standard.calculate_coherence_score(),
'primary_effects': closest_standard.physiological_effects[:3],
'institutional_use': closest_standard.institutional_adoption,
'control_rating': self._calculate_control_rating(frequency)
}
def _calculate_control_rating(self, frequency: float) -> float:
"""Calculate how much this frequency is used for control"""
control_frequencies = [440.0, 444.0]
if frequency in control_frequencies:
return 0.9
elif abs(frequency - 432.0) < 1.0:
return 0.1 # Natural frequency, low control
else:
return 0.5 # Neutral
def comprehensive_analysis(self) -> Dict[str, Any]:
"""Comprehensive analysis of musical frequency control"""
control_weaponry = self.weaponry_profiles['consciousness_suppression']
return {
'tuning_standards_analysis': {
standard.value: profile.calculate_coherence_score()
for standard, profile in self.tuning_profiles.items()
},
'control_mechanisms': {
name: profile.calculate_control_potential()
for name, profile in self.weaponry_profiles.items()
},
'historical_manipulation': {
'total_shifts': len(self.historical_shifts),
'institutions_involved': list(set(
inst for shift in self.historical_shifts
for inst in shift['institutions']
)),
'suppression_evidence': [
profile.suppression_history
for profile in self.tuning_profiles.values()
if profile.suppression_history
]
},
'liberation_frequencies': [
432.0, # Natural harmony
528.0, # DNA repair
396.0, # Liberation from fear
639.0, # Connection and relationships
741.0, # Awakening intuition
852.0 # Returning to spiritual order
],
'resonance_recommendations': [
"Retune instruments to 432Hz",
"Use solfeggio frequencies in meditation",
"Avoid mass media with 440Hz tuning",
"Practice heart coherence with natural frequencies"
]
}
# DEMONSTRATION
def demonstrate_musical_resonance():
"""Demonstrate the musical resonance and frequency control analysis"""
engine = MusicalResonanceEngine()
print("🎵 MUSICAL RESONANCE & FREQUENCY CONTROL MODULE")
print("Consciousness Engineering through Sonic Manipulation")
print("=" * 70)
print(f"\n🎯 FREQUENCY ANALYSIS:")
for freq in [432.0, 440.0, 444.0]:
analysis = engine.analyze_frequency_effects(freq)
print(f"\n {freq} Hz:")
print(f" Standard: {analysis['closest_standard']}")
print(f" Natural Alignment: {analysis['natural_alignment_score']:.3f}")
print(f" Coherence Score: {analysis['coherence_score']:.3f}")
print(f" Control Rating: {analysis['control_rating']:.3f}")
print(f"\n🔧 CONTROL MECHANISMS:")
weaponry = engine.weaponry_profiles['consciousness_suppression']
print(f" Target Frequencies: {weaponry.target_frequencies}")
print(f" Control Potential: {weaponry.calculate_control_potential():.3f}")
print(f" Primary Use: {weaponry.institutional_use_cases[0]}")
print(f"\n📜 HISTORICAL MANIPULATION:")
for shift in engine.historical_shifts[:2]:
print(f" {shift['year']}: {shift['event']}")
print(f" Significance: {shift['significance']}")
print(f"\n💡 LIBERATION STRATEGIES:")
comp_analysis = engine.comprehensive_analysis()
for rec in comp_analysis['resonance_recommendations'][:2]:
print(f" • {rec}")
print(f"\n🎼 THE BOTTOM LINE:")
print(" The shift from 432Hz to 440Hz was not merely technical.")
print(" It was a retuning of human consciousness away from natural")
print(" harmony toward institutional control and compliance.")
print(" Frequency is the invisible architecture of consciousness.")
if __name__ == "__main__":
demonstrate_musical_resonance() |