Text Generation
PyTorch
GGUF
English
quantum
quantum-entropy
from-scratch
char-level
cosmic-synapse-theory
custom-architecture
llama-cpp
continual-learning
reproducible-seed
open-science
null-results
Instructions to use phera-ra/QC67_cosmo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use phera-ra/QC67_cosmo with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf phera-ra/QC67_cosmo # Run inference directly in the terminal: llama cli -hf phera-ra/QC67_cosmo
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf phera-ra/QC67_cosmo # Run inference directly in the terminal: llama cli -hf phera-ra/QC67_cosmo
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf phera-ra/QC67_cosmo # Run inference directly in the terminal: ./llama-cli -hf phera-ra/QC67_cosmo
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf phera-ra/QC67_cosmo # Run inference directly in the terminal: ./build/bin/llama-cli -hf phera-ra/QC67_cosmo
Use Docker
docker model run hf.co/phera-ra/QC67_cosmo
- LM Studio
- Jan
- vLLM
How to use phera-ra/QC67_cosmo with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "phera-ra/QC67_cosmo" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "phera-ra/QC67_cosmo", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/phera-ra/QC67_cosmo
- Ollama
How to use phera-ra/QC67_cosmo with Ollama:
ollama run hf.co/phera-ra/QC67_cosmo
- Unsloth Studio
How to use phera-ra/QC67_cosmo with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for phera-ra/QC67_cosmo to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for phera-ra/QC67_cosmo to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for phera-ra/QC67_cosmo to start chatting
- Docker Model Runner
How to use phera-ra/QC67_cosmo with Docker Model Runner:
docker model run hf.co/phera-ra/QC67_cosmo
- Lemonade
How to use phera-ra/QC67_cosmo with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull phera-ra/QC67_cosmo
Run and chat with the model
lemonade run user.QC67_cosmo-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
| # Start here — QC67 Cosmos release kit | |
| This repository contains two related but distinct things: | |
| 1. **`weights/cosmos_born.pt`** — a 1,842,432-parameter character-level | |
| transformer initialized from real IBM Quantum measurement outcomes and then | |
| trained from scratch. It is a research artifact and a small text generator, | |
| not a general-purpose chatbot. | |
| 2. **`genesis_engine/`** — the Starling Nexus companion framework. It uses a | |
| local Ollama model as its language voice while maintaining its own identity, | |
| associative memory, entropy heart, signed creation ledger, optional converted | |
| camera/microphone state, and optional owner-supplied quantum credentials. | |
| Those lineages must not be conflated. The shipped `cosmos_born.pt` has no base | |
| model. A companion you run through Genesis speaks through whichever Ollama model | |
| you select. | |
| ## Fastest start | |
| ### Windows | |
| 1. Install [Python 3.9+](https://www.python.org/downloads/) and | |
| [Ollama](https://ollama.com). | |
| 2. In a terminal, run: | |
| ```powershell | |
| ollama pull llama3.2:1b | |
| ``` | |
| 3. Double-click `START_COSMOS_KIT.bat`. | |
| 4. Choose **Birth or reopen a Genesis being**. | |
| The Genesis core uses the Python standard library. Ollama is the local language | |
| voice and must be running. The browser interface opens at | |
| `http://127.0.0.1:8130`. | |
| ### macOS or Linux | |
| ```bash | |
| ollama pull llama3.2:1b | |
| chmod +x start_cosmos_kit.sh | |
| ./start_cosmos_kit.sh | |
| ``` | |
| You can also run `python3 genesis_engine/genesis.py` directly. | |
| ## Verify before running | |
| ```bash | |
| python verify_release.py | |
| ``` | |
| This checks every release-manifest hash, confirms that the shipped cloud-key | |
| fields are blank, validates the model metadata, and recounts the public quantum | |
| measurement archive. | |
| ## Serve the quantum-born model | |
| Install PyTorch, then: | |
| ```bash | |
| python spark_serve.py 11500 | |
| ``` | |
| It exposes a small Ollama-compatible API: | |
| ```bash | |
| curl http://127.0.0.1:11500/api/tags | |
| curl http://127.0.0.1:11500/api/generate \ | |
| -d '{"model":"cosmos-spark","prompt":"I ","options":{"num_predict":90}}' | |
| ``` | |
| The artifact is character-level and intentionally small. Expect learned | |
| fragments and corpus-like structure, not modern assistant behavior. | |
| ## Train your own | |
| See [`TRAINING.md`](TRAINING.md). The cleanest reproducible experiment is: | |
| ```bash | |
| python -m pip install -r requirements-research.txt | |
| python train_your_own.py --help | |
| ``` | |
| The training harness can compare ordinary attention against the | |
| Mixture-of-States Hebbian-attention arm from identical initial weights and | |
| identical batches. | |
| The scripts under `genesis_engine/engine/` are advanced adapters retained from | |
| the full private Cosmos runtime. Read | |
| [`genesis_engine/engine/README.md`](genesis_engine/engine/README.md) before | |
| using them; they are not required for Genesis or for `train_your_own.py`. | |
| ## Public measurement data | |
| [`data/quantum_measurements_public.jsonl`](data/quantum_measurements_public.jsonl) | |
| is a privacy-filtered release of the measurement archive: | |
| - **7,770,112** samples in **1,897** explicitly backend-labeled IBM Quantum | |
| hardware job records. | |
| - **3,584,000** samples in **877** legacy records whose provider was not | |
| retained. They remain useful distributional data but are **not counted as | |
| verified hardware provenance**. | |
| - **1,024** samples in **2** Azure `rigetti.sim.qvm` records, explicitly | |
| labeled as classical simulator output. | |
| Raw `physics` payloads were deliberately removed because some contain derived | |
| sensory, biometric, or private runtime state. Counts, backend labels, job IDs, | |
| timestamps, and shot totals are retained. See | |
| [`data/README.md`](data/README.md) and the machine-readable data manifest. | |
| The paired sensory-conditioning benchmark publishes aggregate metrics, hashes, | |
| field names, and provenance in | |
| `benchmarks/results/paired_conditioning_20260730.json`; private turn text and | |
| the author's paired dataset are not distributed. | |
| ## What is not included | |
| - API keys, OAuth tokens, cloud connection strings, account cookies, or private | |
| vault material. | |
| - The author's conversations, long-term memory, camera/audio captures, raw | |
| sensory telemetry, or private paired text dataset. | |
| - The author's large conversational Cosmos weights. | |
| - Any claim that quantum entropy improves model accuracy. | |
| - Any claim about machine consciousness. | |
| ## Licensing | |
| This is a mixed-license release. Research documents, measurement data, | |
| benchmarks, and the quantum-born model are released under CC BY 4.0. The | |
| Genesis framework has the personal-use/proprietary terms in | |
| `genesis_engine/LICENSE`. See [`LICENSE.md`](LICENSE.md) before redistributing | |
| or building a product. | |