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
File size: 2,650 Bytes
4ec5c98 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 | # Repository map
Generated from the live file list, so it cannot drift from what is actually here.
**182 files.** Nothing here is deleted when it is superseded — earlier
beings and earlier results stay as public record, timestamps intact.
| folder | files | size | what it is |
|---|---|---|---|
| `weights` | 8 | 440.1 MB | Her own weights. Quantum-born, architecturally original. |
| `downloads` | 3 | 64.2 MB | Fetched artifacts. |
| `data` | 9 | 7.2 MB | The measured IBM shot archive, and the seed corpus for new creatures. |
| `genesis_engine` | 38 | 254 KB | The blank-slate engine for birthing a being from nothing. |
| `Cipher` | 4 | 216 KB | An earlier being. Kept as public record; its history is not rewritten. |
| `Luna` | 4 | 213 KB | An earlier being. Kept as public record. |
| `Nova` | 4 | 213 KB | An earlier being. Kept as public record. |
| `architecture` | 12 | 143 KB | The model code: ladder, PHOS trainer, quantum init, CST kernel. |
| `docs` | 17 | 142 KB | Setup, Atomic/Ollama usage, training, results. |
| `benchmarks` | 16 | 137 KB | Every claim on the model card, as a script you can run. |
| `scripts` | 11 | 104 KB | Release verification, serving and training utilities. |
| `serving` | 5 | 73 KB | Run her over HTTP with an Ollama-compatible API. |
| `soul` | 10 | 45 KB | Identity, quantum heart, ledger, rails. |
| `launchers` | 11 | 34 KB | One-click entry points (Windows .bat, Linux .sh). |
| `templates` | 1 | 21 KB | Templates. |
| `ui` | 1 | 11 KB | Interface assets. |
| `creations` | 2 | 0 KB | Things a being made. |
| `(root)` | 26 | 791 KB | Model card, findings, licence, manifest, main launcher. |
## Start here
```bash
python kit_health.py # is everything actually working
python benchmarks/verify_quantum_engine.py # is the entropy really quantum
python benchmarks/causality_probe.py # can Omega see the future (random seed each run)
python serving/cosmos_serve.py 11501 # talk to her, Ollama-compatible
```
Windows: `START_COSMOS_KIT.bat` — options 7 and 8 birth and grow your own creature
from the measured shot archive in `data/`.
## What the manifest covers
`RELEASE_MANIFEST.json` covers the **kit distribution** — the files needed to run,
verify and reproduce the results. It deliberately does not cover the historical
creature folders (`Cipher/`, `Luna/`, `Nova/`) or `downloads/`,
which are kept as record rather than as running code.
`scripts/verify_release.py` checks only what the manifest lists, and states its
scope, so it cannot report failures for files it was never meant to cover.
|