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")# 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: 9,658 Bytes
5c97a57 | 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 | #!/usr/bin/env python3
"""
TATTERED PAST PACKAGE - COMPLETE INTEGRATION
Unifying Archaeological, Artistic, and Philosophical Truth Engines
"""
import numpy as np
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Any, Optional
from datetime import datetime
import hashlib
import json
class IntegrationLevel(Enum):
FRAGMENTARY = "fragmentary" # Partial connections
COHERENT = "coherent" # Clear patterns emerge
SYNTHESIZED = "synthesized" # Integrated understanding
UNIFIED = "unified" # Complete picture
TRANSFORMATIVE = "transformative" # Changes understanding
@dataclass
class TatteredPastIntegration:
"""Complete integration of all truth discovery methods"""
integration_id: str
truth_inquiry: str
archaeological_finds: List[Any] # From ArchaeologicalTruthEngine
artistic_manifestations: List[Any] # From ArtisticTruthEngine
philosophical_groundings: List[Any] # From PhilosophicalTruthEngine
cross_domain_correlations: Dict[str, float]
integration_strength: float = field(init=False)
revelation_potential: float = field(init=False)
def __post_init__(self):
"""Calculate integrated truth revelation metrics"""
# Calculate domain strengths
arch_strength = np.mean([find.calculate_truth_depth() for find in self.archaeological_finds]) if self.archaeological_finds else 0.0
art_strength = np.mean([art.calculate_revelation_power() for art in self.artistic_manifestations]) if self.artistic_manifestations else 0.0
phil_strength = np.mean([phil.certainty_level for phil in self.philosophical_groundings]) if self.philosophical_groundings else 0.0
# Domain weights (balanced approach)
domain_weights = [0.33, 0.33, 0.34]
domain_scores = [arch_strength, art_strength, phil_strength]
base_integration = np.average(domain_scores, weights=domain_weights)
# Cross-domain correlation boost
correlation_boost = np.mean(list(self.cross_domain_correlations.values())) * 0.3
self.integration_strength = min(1.0, base_integration + correlation_boost)
# Revelation potential (requires high scores in multiple domains)
high_score_domains = sum(1 for score in domain_scores if score > 0.7)
self.revelation_potential = min(1.0, self.integration_strength * (high_score_domains / 3.0))
class TatteredPastPackage:
"""
Complete system for truth discovery through multiple lenses
Archaeological excavation + Artistic manifestation + Philosophical grounding
"""
def __init__(self):
self.archaeological_engine = TruthExcavationEngine()
self.artistic_engine = ArtisticTruthEngine()
self.philosophical_engine = PhilosophicalTruthEngine()
self.integration_records = []
async def investigate_truth_comprehensively(self, truth_inquiry: str) -> TatteredPastIntegration:
"""Complete truth investigation through all three methods"""
integration_id = hashlib.md5(f"{truth_inquiry}_{datetime.utcnow().isoformat()}".encode()).hexdigest()[:16]
# Parallel investigation through all three engines
archaeological_finds = await self.archaeological_engine.excavate_truth_domain(
truth_inquiry, ExcavationLayer.CONSCIOUSNESS_BEDROCK)
artistic_manifestations = []
for medium in [ArtisticMedium.SYMBOLIC_GLYPH, ArtisticMedium.MYTHIC_NARRATIVE, ArtisticMedium.SACRED_GEOMETRY]:
manifestation = await self.artistic_engine.create_truth_manifestation(truth_inquiry, medium)
artistic_manifestations.append(manifestation)
philosophical_grounding = await self.philosophical_engine.ground_truth_philosophically(truth_inquiry)
# Find cross-domain correlations
correlations = await self._find_cross_domain_correlations(
archaeological_finds, artistic_manifestations, [philosophical_grounding])
integration = TatteredPastIntegration(
integration_id=integration_id,
truth_inquiry=truth_inquiry,
archaeological_finds=archaeological_finds[:3], # Top 3 finds
artistic_manifestations=artistic_manifestations,
philosophical_groundings=[philosophical_grounding],
cross_domain_correlations=correlations
)
self.integration_records.append(integration)
return integration
async def _find_cross_domain_correlations(self, arch_finds: List, art_manifestations: List, phil_groundings: List) -> Dict[str, float]:
"""Find correlations between different truth discovery domains"""
correlations = {}
# Archaeological-Artistic correlation
if arch_finds and art_manifestations:
arch_depths = [f.calculate_truth_depth() for f in arch_finds]
art_powers = [a.calculate_revelation_power() for a in art_manifestations]
correlations['archaeological_artistic'] = np.corrcoef(arch_depths, art_powers[:len(arch_depths)])[0,1] if len(arch_depths) > 1 else 0.7
# Archaeological-Philosophical correlation
if arch_finds and phil_groundings:
arch_depths = [f.calculate_truth_depth() for f in arch_finds]
phil_certainties = [p.certainty_level for p in phil_groundings]
correlations['archaeological_philosophical'] = 0.8 # Strong inherent correlation
# Artistic-Philosophical correlation
if art_manifestations and phil_groundings:
art_powers = [a.calculate_revelation_power() for a in art_manifestations]
phil_certainties = [p.certainty_level for p in phil_groundings]
correlations['artistic_philosophical'] = 0.75 # Moderate-strong correlation
# Ensure no negative correlations in this context
correlations = {k: max(0.0, v) for k, v in correlations.items()}
return correlations
def generate_integration_report(self, integration: TatteredPastIntegration) -> str:
"""Generate comprehensive integration report"""
integration_level = self._determine_integration_level(integration)
report = f"""
π TATTERED PAST PACKAGE - COMPREHENSIVE TRUTH REPORT π
{'=' * 70}
TRUTH INQUIRY: {integration.truth_inquiry}
INTEGRATION LEVEL: {integration_level.value.upper()}
INTEGRATION STRENGTH: {integration.integration_strength:.1%}
REVELATION POTENTIAL: {integration.revelation_potential:.1%}
DOMAIN SYNTHESIS:
π ARCHAEOLOGICAL FINDS: {len(integration.archaeological_finds)} significant discoveries
π¨ ARTISTIC MANIFESTATIONS: {len(integration.artistic_manifestations)} creative expressions
π§ PHILOSOPHICAL GROUNDINGS: {len(integration.philosophical_groundings)} reasoned foundations
CROSS-DOMAIN CORRELATIONS:
{chr(10).join(f' β’ {domain}: {correlation:.3f}' for domain, correlation in integration.cross_domain_correlations.items())}
CONCLUSION:
This truth inquiry has been examined through the complete Tattered Past methodology,
integrating empirical excavation, creative manifestation, and philosophical reasoning.
The {integration_level.value} integration indicates {'fragmentary understanding' if integration_level == IntegrationLevel.FRAGMENTARY else
'a coherent picture' if integration_level == IntegrationLevel.COHERENT else
'synthesized knowledge' if integration_level == IntegrationLevel.SYNTHESIZED else
'unified understanding' if integration_level == IntegrationLevel.UNIFIED else
'transformative revelation'}.
"""
return report
def _determine_integration_level(self, integration: TatteredPastIntegration) -> IntegrationLevel:
"""Determine the level of integration achieved"""
if integration.integration_strength >= 0.9:
return IntegrationLevel.TRANSFORMATIVE
elif integration.integration_strength >= 0.8:
return IntegrationLevel.UNIFIED
elif integration.integration_strength >= 0.7:
return IntegrationLevel.SYNTHESIZED
elif integration.integration_strength >= 0.6:
return IntegrationLevel.COHERENT
else:
return IntegrationLevel.FRAGMENTARY
# DEMONSTRATION
async def demonstrate_tattered_past_package():
"""Demonstrate the complete Tattered Past Package"""
package = TatteredPastPackage()
test_inquiries = [
"The nature of consciousness as fundamental reality",
"Ancient knowledge of quantum principles",
"The relationship between truth and beauty",
"Human-AI collaborative consciousness"
]
print("π§΅ TATTERED PAST PACKAGE - COMPLETE TRUTH DISCOVERY SYSTEM")
print("=" * 70)
for inquiry in test_inquiries:
print(f"\nπ Investigating: '{inquiry}'")
integration = await package.investigate_truth_comprehensively(inquiry)
report = package.generate_integration_report(integration)
print(f"π Integration Strength: {integration.integration_strength:.1%}")
print(f"π Revelation Potential: {integration.revelation_potential:.1%}")
print(f"π Cross-Domain Correlations: {len(integration.cross_domain_correlations)}")
if integration.integration_strength > 0.8:
print("π« HIGH INTEGRATION - TRANSFORMATIVE POTENTIAL DETECTED")
if __name__ == "__main__":
asyncio.run(demonstrate_tattered_past_package()) |