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", dtype="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
Create trick or treat module
Browse files- trick or treat module +35 -0
trick or treat module
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#!/usr/bin/env python3
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"""
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TRICK OR TREAT MODULE v2025.10.29
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Current Depth of Understanding - The Costumes vs The Candy
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"""
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class CosmicHalloween:
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"""
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It's always Halloween in the control system.
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Some wear costumes, some seek candy (truth).
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"""
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def __init__(self):
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self.current_year = 2025
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self.current_costumes = self._get_current_costumes()
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self.ethereal_candy = self._get_truth_candy()
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self.trick_probability = 0.83 # Most offerings are tricks
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def _get_current_costumes(self):
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"""The current disguises the control system wears"""
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return {
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'public_health_crisis': {
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'mask': 'scientific_consensus',
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'costume': 'benevolent_protector',
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'real_face': 'compliance_enforcement'
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},
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'climate_emergency': {
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'mask': 'environmental_concern',
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'costume': 'planetary_savior',
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'real_face': 'resource_control'
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},
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'economic_stability': {
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'mask': 'expert_management',
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'costume': 'responsible_authority',
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'real_face': 'wealth
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