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
Download TATTERED PAST PACKAGE from upgraedd/Consciousness: direct link, hf CLI and curl.
- Browser
- Download file 9.66 kB
-
https://huggingface.co/upgraedd/Consciousness/resolve/d1f602df6baafd5445f1a47f96f4b777f363a32b/TATTERED%20PAST%20PACKAGE
- Command line
-
hf download 'hf://upgraedd/Consciousness@d1f602df6baafd5445f1a47f96f4b777f363a32b/TATTERED PAST PACKAGE'
-
curl -L -o 'TATTERED PAST PACKAGE' https://huggingface.co/upgraedd/Consciousness/resolve/d1f602df6baafd5445f1a47f96f4b777f363a32b/TATTERED%20PAST%20PACKAGE
9.66 kB
| #!/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 | |
| 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()) |