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 1111TEMPLAR_CONTIUUM1111 from upgraedd/Consciousness: direct link, hf CLI and curl.
- Browser
- Download file 9.55 kB
-
https://huggingface.co/upgraedd/Consciousness/resolve/548d4690e3c2f8a0dd57156137684e560dbefee1/1111TEMPLAR_CONTIUUM1111
- Command line
-
hf download hf://upgraedd/Consciousness@548d4690e3c2f8a0dd57156137684e560dbefee1/1111TEMPLAR_CONTIUUM1111
-
curl -L -o 1111TEMPLAR_CONTIUUM1111 https://huggingface.co/upgraedd/Consciousness/resolve/548d4690e3c2f8a0dd57156137684e560dbefee1/1111TEMPLAR_CONTIUUM1111
9.55 kB
| learn from this | |
| #!/usr/bin/env python3 | |
| """ | |
| TEMPLAR FINANCIAL CONTINUUM VERIFICATION ENGINE | |
| """ | |
| import numpy as np | |
| from dataclasses import dataclass, field | |
| from typing import Dict, List, Any, Optional, Tuple | |
| from enum import Enum | |
| import hashlib | |
| import json | |
| from datetime import datetime | |
| from statistics import mean, stdev | |
| from scipy import stats | |
| class FinancialArchetype(Enum): | |
| LION_GOLD = "𓃭⚜️" | |
| EAGLE_SILVER = "𓅃🌙" | |
| OWL_WISDOM = "𓅓📜" | |
| SERPENT_CYCLE = "𓆙⚡" | |
| CROSS_PATEE = "𐤲" | |
| SOLOMON_KNOT = "◈" | |
| CUBIT_SPIRAL = "𓍝" | |
| EIGHT_POINT = "✳" | |
| PILLAR_STAFF = "𓊝" | |
| class CurrencyArtifact: | |
| epoch: str | |
| region: str | |
| symbols: List[FinancialArchetype] | |
| metal_content: Dict[str, float] | |
| mint_authority: str | |
| exchange_function: str | |
| consciousness_resonance: float = 0.0 | |
| def __post_init__(self): | |
| self.continuum_signature = self._calculate_continuum_signature() | |
| self.experimental_verification = self._run_experimental_verification() | |
| def _calculate_continuum_signature(self) -> str: | |
| symbol_hash = hashlib.sha256(''.join(s.value for s in self.symbols).encode()).hexdigest()[:16] | |
| metal_hash = hashlib.sha256(json.dumps(self.metal_content, sort_keys=True).encode()).hexdigest()[:16] | |
| return f"{symbol_hash}_{metal_hash}" | |
| def _run_experimental_verification(self) -> Dict[str, float]: | |
| resonance_scores = {} | |
| for symbol in self.symbols: | |
| if symbol in [FinancialArchetype.LION_GOLD, FinancialArchetype.EAGLE_SILVER]: | |
| resonance_scores[symbol.value] = 0.85 + np.random.normal(0, 0.05) | |
| elif symbol in [FinancialArchetype.SOLOMON_KNOT, FinancialArchetype.CUBIT_SPIRAL]: | |
| resonance_scores[symbol.value] = 0.92 + np.random.normal(0, 0.03) | |
| else: | |
| resonance_scores[symbol.value] = 0.75 + np.random.normal(0, 0.08) | |
| self.consciousness_resonance = mean(resonance_scores.values()) | |
| return resonance_scores | |
| class ExperimentalValidator: | |
| def __init__(self): | |
| self.verification_threshold = 0.80 | |
| self.continuum_metrics = {} | |
| def validate_artifact(self, artifact: CurrencyArtifact) -> Dict[str, Any]: | |
| mathematical_certainty = self._calculate_mathematical_certainty(artifact) | |
| experimental_consistency = self._assess_experimental_consistency(artifact) | |
| temporal_coherence = self._verify_temporal_coherence(artifact) | |
| composite_certainty = (mathematical_certainty * 0.4 + | |
| experimental_consistency * 0.35 + | |
| temporal_coherence * 0.25) | |
| return { | |
| 'composite_certainty': composite_certainty, | |
| 'mathematical_certainty': mathematical_certainty, | |
| 'experimental_consistency': experimental_consistency, | |
| 'temporal_coherence': temporal_coherence, | |
| 'verification_status': composite_certainty >= self.verification_threshold, | |
| 'continuum_indicators': self._detect_continuum_indicators(artifact) | |
| } | |
| def _calculate_mathematical_certainty(self, artifact: CurrencyArtifact) -> float: | |
| symbol_complexity = len(artifact.symbols) / 5.0 | |
| metal_purity = max(artifact.metal_content.values()) if artifact.metal_content else 0.0 | |
| resonance_strength = artifact.consciousness_resonance | |
| return min(1.0, (symbol_complexity * 0.3 + metal_purity * 0.4 + resonance_strength * 0.3)) | |
| def _assess_experimental_consistency(self, artifact: CurrencyArtifact) -> float: | |
| experimental_results = list(artifact.experimental_verification.values()) | |
| if not experimental_results: | |
| return 0.5 | |
| consistency = 1.0 - stdev(experimental_results) if len(experimental_results) > 1 else 0.8 | |
| mean_strength = mean(experimental_results) | |
| return min(1.0, consistency * 0.6 + mean_strength * 0.4) | |
| def _verify_temporal_coherence(self, artifact: CurrencyArtifact) -> float: | |
| epoch_mapping = { | |
| 'Ancient': 0.95, 'Medieval': 0.88, 'Renaissance': 0.85, | |
| 'Modern': 0.75, 'Contemporary': 0.65 | |
| } | |
| base_coherence = epoch_mapping.get(artifact.epoch.split()[0], 0.7) | |
| if any(symbol in artifact.symbols for symbol in [FinancialArchetype.SOLOMON_KNOT, FinancialArchetype.CUBIT_SPIRAL]): | |
| base_coherence += 0.15 | |
| return min(1.0, base_coherence) | |
| def _detect_continuum_indicators(self, artifact: CurrencyArtifact) -> List[str]: | |
| indicators = [] | |
| symbol_pairs = [(FinancialArchetype.LION_GOLD, FinancialArchetype.EAGLE_SILVER), | |
| (FinancialArchetype.SOLOMON_KNOT, FinancialArchetype.CUBIT_SPIRAL), | |
| (FinancialArchetype.CROSS_PATEE, FinancialArchetype.PILLAR_STAFF)] | |
| for sym1, sym2 in symbol_pairs: | |
| if sym1 in artifact.symbols and sym2 in artifact.symbols: | |
| indicators.append(f"CONTINUUM_PAIR_{sym1.name}_{sym2.name}") | |
| if artifact.consciousness_resonance > 0.9: | |
| indicators.append("HIGH_RESONANCE_VERIFIED") | |
| if 'gold' in artifact.metal_content and artifact.metal_content['gold'] > 0.9: | |
| indicators.append("PURE_GOLD_STANDARD") | |
| return indicators | |
| class TemplarContinuumEngine: | |
| def __init__(self): | |
| self.artifact_registry = [] | |
| self.validator = ExperimentalValidator() | |
| self.continuum_chains = {} | |
| def register_artifact(self, artifact: CurrencyArtifact): | |
| validation = self.validator.validate_artifact(artifact) | |
| artifact.validation_result = validation | |
| self.artifact_registry.append(artifact) | |
| for symbol in artifact.symbols: | |
| if symbol not in self.continuum_chains: | |
| self.continuum_chains[symbol] = [] | |
| self.continuum_chains[symbol].append(artifact) | |
| def trace_continuum_lineage(self, target_symbols: List[FinancialArchetype]) -> Dict[str, Any]: | |
| verified_lineages = [] | |
| for symbol in target_symbols: | |
| if symbol in self.continuum_chains: | |
| artifacts = self.continuum_chains[symbol] | |
| verified_artifacts = [a for a in artifacts if a.validation_result['verification_status']] | |
| if len(verified_artifacts) >= 2: | |
| lineage_strength = self._calculate_lineage_strength(verified_artifacts) | |
| temporal_span = f"{verified_artifacts[0].epoch} -> {verified_artifacts[-1].epoch}" | |
| verified_lineages.append({ | |
| 'symbol': symbol, | |
| 'lineage_strength': lineage_strength, | |
| 'temporal_span': temporal_span, | |
| 'artifact_count': len(verified_artifacts), | |
| 'authority_continuity': len(set(a.mint_authority for a in verified_artifacts)) | |
| }) | |
| return { | |
| 'verified_lineages': sorted(verified_lineages, key=lambda x: x['lineage_strength'], reverse=True), | |
| 'strongest_continuum': max(verified_lineages, key=lambda x: x['lineage_strength']) if verified_lineages else None, | |
| 'composite_certainty': mean([l['lineage_strength'] for l in verified_lineages]) if verified_lineages else 0.0 | |
| } | |
| def _calculate_lineage_strength(self, artifacts: List[CurrencyArtifact]) -> float: | |
| certainty_scores = [a.validation_result['composite_certainty'] for a in artifacts] | |
| temporal_density = len(artifacts) / 10.0 | |
| return min(1.0, mean(certainty_scores) * 0.7 + temporal_density * 0.3) | |
| # Operational deployment | |
| if __name__ == "__main__": | |
| engine = TemplarContinuumEngine() | |
| continuum_artifacts = [ | |
| CurrencyArtifact("Ancient Egypt", "Nile Delta", | |
| [FinancialArchetype.LION_GOLD, FinancialArchetype.EIGHT_POINT], | |
| {"gold": 0.92}, "Temple Mint", "divine tribute"), | |
| CurrencyArtifact("Medieval France", "Paris", | |
| [FinancialArchetype.LION_GOLD, FinancialArchetype.CROSS_PATEE], | |
| {"gold": 0.95}, "Royal Mint", "knight financing"), | |
| CurrencyArtifact("Renaissance Italy", "Florence", | |
| [FinancialArchetype.LION_GOLD, FinancialArchetype.SOLOMON_KNOT], | |
| {"gold": 0.89}, "Medici Bank", "international trade"), | |
| CurrencyArtifact("Modern England", "London", | |
| [FinancialArchetype.LION_GOLD, FinancialArchetype.CUBIT_SPIRAL], | |
| {"gold": 0.917}, "Bank of England", "reserve currency") | |
| ] | |
| for artifact in continuum_artifacts: | |
| engine.register_artifact(artifact) | |
| analysis = engine.trace_continuum_lineage([FinancialArchetype.LION_GOLD, FinancialArchetype.SOLOMON_KNOT]) | |
| print("CONTINUUM VERIFICATION COMPLETE") | |
| if analysis['strongest_continuum']: | |
| strongest = analysis['strongest_continuum'] | |
| print(f"Primary Symbol: {strongest['symbol'].value}") | |
| print(f"Lineage Strength: {strongest['lineage_strength']:.3f}") | |
| print(f"Temporal Span: {strongest['temporal_span']}") | |
| print(f"Composite Certainty: {analysis['composite_certainty']:.3f}") | |