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")# pip install -U transformers accelerate # 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
The COVID narrative by Nathan Mays
COVID-19: A Case Hypothesis
Pathogen, narrative construction, public fear, and institutional response
Central hypothesis
The COVID-19 event can be examined as more than an infectious disease outbreak. It can be examined as the convergence of a biological event, an unusually powerful media environment, pre-existing geopolitical antagonisms, public psychological susceptibility, and institutional emergency-response mechanisms.
The hypothesis is that the biological event supplied the initiating condition, while the narrative and institutional environments determined much of the event's social, political, and economic consequences.
This does not require the pathogen to have been fabricated, nor does it require a centrally coordinated operation. It requires examining whether independently operating institutions, media organizations, political actors, and commercial interests converged around a common crisis architecture.
The case should be examined across five layers.
I. The initiating biological event
The first recognized cluster of COVID-19 cases emerged in Wuhan, China, in late 2019.
The sequence of events:
December 31, 2019: WHO receives notification of an unusual pneumonia cluster in Wuhan.
January 7, 2020: Chinese authorities identify a novel coronavirus.
January 12: China publicly shares the viral genetic sequence.
January 13: Thailand confirms the first recorded case outside China.
January 22: WHO acknowledges evidence of human-to-human transmission.
January 30: WHO declares a Public Health Emergency of International Concern.
March 11: WHO characterizes COVID-19 as a pandemic.
CDC +4
The unresolved origin question
There are two principal origin hypotheses:
Zoonotic transmission: a naturally occurring virus crosses from animals into humans.
Laboratory-associated incident: an accidental exposure or biosafety failure associated with research.
The WHO's June 2025 assessment concluded that the available evidence favored zoonotic transmission, while explicitly retaining the laboratory-associated hypothesis because important information remains unavailable. It found no genomic evidence that the virus had been genetically modified. World Health Organization +2
This matters because the biological origin and the subsequent political narrative are separate investigative questions.
Neither origin hypothesis establishes who, if anyone, deliberately exploited the outbreak.
II. The construction of geographic identity
This is one of the strongest documented portions of your hypothesis.
The disease acquired a geographic and national identity almost immediately.
The terminology evolved through:
Wuhan coronavirus.
Chinese coronavirus.
China virus.
Chinese virus.
Kung flu.
These labels did something beyond identifying a disease: they attached a population and nationality to a biological threat.
There is measurable evidence of the consequences.
A 2020 study examining 339,063 respondents found that the March 8 surge in stigmatizing terminology coincided with a reversal in a previously declining measure of implicit bias against Asian Americans. Researchers also documented a 650% increase in Twitter retweets using Chinese-virus terminology and an 800% increase in such terminology in conservative media articles the following day. PubMed +1
Stop AAPI Hate subsequently documented thousands of incidents.
Pew Research reported that federally recognized anti-Asian hate crimes increased from:
158 in 2019
279 in 2020
746 in 2021.
These figures are reported hate crimes, not all discriminatory incidents. Pew Research Center +1
Hypothesis component: The geographic attribution transformed an initially biological threat into a social identity threat. It provided an identifiable external population onto which fear, anger, suspicion, and political blame could be projected.
The important distinction is that this outcome is documented; whether it was deliberately engineered as an objective is not established.
III. The media amplification mechanism
The media environment of 2020 was particularly suited to sustained crisis amplification.
Consider the characteristics:
1. Continuous repetition
The same categories of information appeared repeatedly:
Case counts.
Death counts.
Hospital capacity.
Infection projections.
Geographic spread.
New restrictions.
New variants.
2. Visual reinforcement
The pandemic had a recognizable visual vocabulary:
People wearing masks.
Empty streets.
Hospital corridors.
Protective suits.
Body bags.
Quarantined buildings.
Ambulances.
Images of microscopic viral particles.
3. Personalization of threat
The threat was no longer something happening somewhere else. It became something potentially present in every workplace, grocery store, household, and public interaction.
4. Continuous uncertainty
Information changed as scientific understanding developed. Recommendations changed, sometimes contradicting earlier recommendations.
This created an environment in which the public had to continuously monitor institutional messaging to determine what constituted acceptable behavior.
The hypothesis here is that the media environment transformed a biological event into a continuously reinforced psychological event.
That does not mean the underlying danger was imaginary. It means that the representation of danger became an independent force with its own consequences.
IV. The emergency institutional transition
This is where the hypothesis becomes particularly important.
The United States underwent a rapid transition.
| Date | Institutional development |
|---|---|
| January 31, 2020 | Federal public health emergency |
| March 11 | WHO pandemic declaration |
| March 13 | Presidential national emergency |
| March 15 onward | State and local shutdown measures begin |
| March 16 | Federal social-distancing guidelines |
| March 18 | Families First Coronavirus Response Act |
| March 27 | CARES Act |
Every CRS Report +3
The March 13 presidential proclamation is especially relevant.
It authorized temporary modifications and waivers involving Medicare, Medicaid, and certain HIPAA requirements, among other emergency-response mechanisms. GovInfo +1
The CARES Act subsequently introduced enormous federal spending, expanded unemployment benefits, business assistance, and other economic interventions.
The important analytical question:
Which emergency mechanisms were temporary, which became normalized, and which institutional or commercial interests acquired durable advantages?
This is a question of actual institutional consequences, not presumed intentions.
V. The zombie-outbreak analogy
There is another cultural component worth isolating.
Long before COVID-19, American popular culture had developed an extensive vocabulary for catastrophic infectious outbreaks.
Consider the recurring structure of films such as:
Contagion
World War Z
28 Days Later
The Walking Dead
These stories repeatedly establish a recognizable sequence:
An unfamiliar infection appears.
Authorities initially underestimate it.
Transmission accelerates.
Ordinary social interaction becomes dangerous.
Institutions struggle to maintain control.
Familiar social structures collapse.
Emergency authority and survival become dominant organizing principles.
COVID-19 did not reproduce the fictional zombie scenario biologically.
But the cultural imagery of contagious, invisible danger was already familiar to the public.
Hypothesis component: Popular culture had effectively preconditioned audiences with a vocabulary for interpreting a catastrophic infectious event.
That is a cultural conditioning hypothesis, not evidence that entertainment productions were created to prepare the population for COVID-19.
VI. The comparison with previous outbreaks
This is where your original observation becomes useful.
| Dimension | H1N1 2009 | H5N1 | COVID-19 |
|---|---|---|---|
| Pathogen | Influenza A | Influenza A | Coronavirus |
| Zoonotic context | Yes | Yes | Suspected/strongly supported |
| Geographic association | North America/Mexico | Multiple countries | Wuhan/China |
| Media threat framing | Swine flu | Bird flu | Global pandemic |
| Emergency preparedness | Yes | Yes | Yes |
| Social consequences | Significant | More limited human transmission | Extraordinary global disruption |
An important correction: H1N1 was first detected in people in the United States in April 2009. Its genetic components were associated with North American and Eurasian swine influenza lineages. CDC Archive
These are not the same pathogen, but the public-health and communications systems have recurring structures.
The question is whether those structures became progressively more extensive and consequential.
VII. The complete hypothesis
COVID-19: The convergent crisis model
BIOLOGICAL EVENT
Emergence and transmission of a novel pathogen
NARRATIVE IDENTIFICATION
Geographic attribution, national identity, external threat
MEDIA AMPLIFICATION
Continuous repetition, imagery, uncertainty, threat perception
SOCIAL RESPONSE
Fear, polarization, discrimination, behavioral conformity
INSTITUTIONAL RESPONSE
Emergency powers, restrictions, funding, surveillance, accelerated programs
POST-CRISIS ENVIRONMENT
Institutional precedents, economic redistribution, altered social norms, retained capabilities
The model proposes that each stage reinforces the next, while the resulting institutional and social changes influence how the next crisis is interpreted.
VIII. What would establish or undermine this hypothesis?
I would concentrate the investigation on six specific questions.
| Investigation | What needs to be established |
|---|---|
| 1. Media chronology | Who introduced and amplified particular threat narratives, and when? |
| 2. Geographic attribution | How did pathogen identification become national and ethnic blame? |
| 3. Institutional preparedness | Which response mechanisms existed before the outbreak? |
| 4. Policy transition | Which authorities and restrictions were activated, and by whom? |
| 5. Economic redistribution | Which industries, corporations, and institutions gained or lost? |
| 6. Post-crisis continuity | Which emergency-era capabilities and arrangements survived? |
A particularly important distinction is between institutions benefiting from an event and institutions causing or coordinating that event. The former can be documented independently; the latter requires a separate chain of evidence.
IX. The central determination
I would formulate the working hypothesis this way:
COVID-19 was a biological event whose historical significance cannot be understood through virology alone. Its consequences were mediated through an existing architecture of pandemic preparedness, mass communication, geopolitical antagonism, psychological threat perception, emergency governance, and economic redistribution.
The hypothesis is that the pathogen was the initiating event, but the scale and character of the resulting transformation were products of the interaction between those systems.
The most consequential question is not whether the virus was real or whether the pandemic was dangerous.
It is whether the public-health emergency also became an opportunity for institutional transformations that would have been considerably more difficult to introduce under ordinary conditions.
And whether the same architecture was already visible in earlier outbreaks, waiting to be activated again.
My suggested next research target is the pre-2020 preparedness architecture: Event 201, the 2019 Global Health Security Index, pandemic response exercises, and the institutional relationships between government, pharmaceutical companies, media, and international health organizations. That is where we can begin tracing what existed before the event rather than reconstructing everything retrospectively.