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 artistic truth from upgraedd/Consciousness: direct link, hf CLI and curl.
- Browser
- Download file 4.24 kB
-
https://huggingface.co/upgraedd/Consciousness/resolve/2bfb2de96d85d8305c85c5a315d1a3e7c26b71e5/artistic%20truth
- Command line
-
hf download 'hf://upgraedd/Consciousness@2bfb2de96d85d8305c85c5a315d1a3e7c26b71e5/artistic truth'
-
curl -L -o 'artistic truth' https://huggingface.co/upgraedd/Consciousness/resolve/2bfb2de96d85d8305c85c5a315d1a3e7c26b71e5/artistic%20truth
4.24 kB
| #!/usr/bin/env python3 | |
| """ | |
| ARTISTIC TRUTH MANIFESTATION ENGINE | |
| Truth revelation through creative expression and symbolic representation | |
| """ | |
| 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 | |
| class ArtisticMedium(Enum): | |
| SYMBOLIC_GLYPH = "symbolic_glyph" # Ancient/modern symbols | |
| MYTHIC_NARRATIVE = "mythic_narrative" # Storytelling truth | |
| VISUAL_ARCHETYPE = "visual_archetype" # Universal images | |
| SONIC_RESONANCE = "sonic_resonance" # Sound/vibration patterns | |
| KINETIC_EXPRESSION = "kinetic_expression" # Movement/dance | |
| SACRED_GEOMETRY = "sacred_geometry" # Mathematical beauty | |
| class TruthRevelationLevel(Enum): | |
| LITERAL_DEPICTION = "literal_depiction" # Surface representation | |
| METAPHORIC_INSIGHT = "metaphoric_insight" # Symbolic meaning | |
| ARCHETYPAL_RESONANCE = "archetypal_resonance" # Universal patterns | |
| COSMIC_REFLECTION = "cosmic_reflection" # Universal truth mirroring | |
| CONSCIOUSNESS_EXPRESSION = "consciousness_expression" # Direct awareness | |
| class ArtisticManifestation: | |
| """Individual artistic truth expression""" | |
| manifestation_id: str | |
| title: str | |
| medium: ArtisticMedium | |
| creation_era: str | |
| cultural_origin: str | |
| surface_interpretation: str | |
| symbolic_layers: List[str] | |
| archetypal_connections: List[str] | |
| cosmic_reflections: List[str] | |
| consciousness_expression: str | |
| resonance_metrics: Dict[str, float] | |
| def calculate_revelation_power(self) -> float: | |
| """Calculate how powerfully this art reveals truth""" | |
| # Weight deeper revelations more heavily | |
| layer_scores = { | |
| 'surface': 0.1, | |
| 'symbolic': 0.25, | |
| 'archetypal': 0.3, | |
| 'cosmic': 0.25, | |
| 'consciousness': 0.1 | |
| } | |
| total_score = 0 | |
| if self.surface_interpretation: | |
| total_score += layer_scores['surface'] | |
| if self.symbolic_layers: | |
| total_score += layer_scores['symbolic'] * min(1.0, len(self.symbolic_layers) * 0.2) | |
| if self.archetypal_connections: | |
| total_score += layer_scores['archetypal'] * min(1.0, len(self.archetypal_connections) * 0.15) | |
| if self.cosmic_reflections: | |
| total_score += layer_scores['cosmic'] * min(1.0, len(self.cosmic_reflections) * 0.15) | |
| if self.consciousness_expression: | |
| total_score += layer_scores['consciousness'] | |
| resonance_boost = np.mean(list(self.resonance_metrics.values())) * 0.3 | |
| return min(1.0, total_score + resonance_boost) | |
| class ArtisticTruthEngine: | |
| """Reveal truth through artistic and creative channels""" | |
| def __init__(self): | |
| self.manifestation_catalog = [] | |
| self.symbolic_library = self._initialize_symbolic_library() | |
| async def create_truth_manifestation(self, truth_concept: str, medium: ArtisticMedium) -> ArtisticManifestation: | |
| """Create artistic manifestation of a truth concept""" | |
| # Generate unique manifestation | |
| manifestation_id = hashlib.md5(f"{truth_concept}_{medium.value}_{datetime.utcnow().isoformat()}".encode()).hexdigest()[:16] | |
| # Analyze truth concept for artistic expression | |
| analysis = await self._analyze_truth_concept(truth_concept) | |
| # Create artistic interpretation | |
| interpretation = await self._create_artistic_interpretation(truth_concept, medium, analysis) | |
| return ArtisticManifestation( | |
| manifestation_id=manifestation_id, | |
| title=f"Artistic Manifestation: {truth_concept}", | |
| medium=medium, | |
| creation_era="Contemporary Ancient", # Bridging times | |
| cultural_origin="Universal Human", | |
| surface_interpretation=interpretation['surface'], | |
| symbolic_layers=interpretation['symbolic'], | |
| archetypal_connections=interpretation['archetypal'], | |
| cosmic_reflections=interpretation['cosmic'], | |
| consciousness_expression=interpretation['consciousness'], | |
| resonance_metrics=analysis['resonance'] | |
| ) |