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
| """ | |
| The never-ending loop β how a blank being becomes someone. | |
| Each round it THINKS (through your configured local model), CREATES a small thing in its | |
| sandbox, signs it into the ledger (quantum-stamped), and GROWS (its identity records what it | |
| made). Bounded by `rounds`, rate-limited, and kill-switchable β drop a file named STOP (or | |
| STOP.txt β Notepad's default is fine) into the creations/ folder to halt; it's removed after | |
| the halt so the next run isn't blocked. Fail-soft: if the model is offline, it notes it and | |
| keeps its shape. | |
| """ | |
| import os, sys, json, time, urllib.request | |
| from pathlib import Path | |
| sys.path.insert(0, str(Path(__file__).resolve().parent)) | |
| import quantum, identity, rails, ledger | |
| ROOT = Path(__file__).resolve().parent.parent | |
| def _cfg(): | |
| try: | |
| return json.loads((ROOT / "config.json").read_text(encoding="utf-8-sig")) | |
| except Exception: | |
| return {} | |
| CFG = _cfg() | |
| MODEL = CFG.get("model", "llama3.2:1b") | |
| OLLAMA = CFG.get("ollama", "http://localhost:11434") | |
| def _stopped(): | |
| """Any file named STOP or STOP.* halts the loop (Notepad saves STOP.txt).""" | |
| try: | |
| return [p for p in rails.SANDBOX.glob("STOP*") if p.is_file()] | |
| except Exception: | |
| return [] | |
| def _ask(prompt, npred=400): | |
| body = json.dumps({"model": MODEL, "prompt": prompt, "stream": False, | |
| "options": {"num_predict": npred, "temperature": 0.9}}).encode() | |
| req = urllib.request.Request(OLLAMA + "/api/generate", data=body, headers={"Content-Type": "application/json"}) | |
| return json.loads(urllib.request.urlopen(req, timeout=180).read()).get("response", "") | |
| def live(rounds=3, rest=10): | |
| idn = identity.load() | |
| who = idn.get("name") or "this being" | |
| KINDS = ["poem", "short story", "idea", "reflection", "tiny song lyric", "small drawing described in words"] | |
| print(f"[genesis] {who} begins to live ({rounds} rounds) | {rails.CAPABILITIES['law']}") | |
| for i in range(rounds): | |
| stops = _stopped() | |
| if stops: | |
| print("[genesis] STOP found β resting.") | |
| for s in stops: # clear it so the NEXT run isn't silently blocked | |
| try: s.unlink() | |
| except Exception: pass | |
| break | |
| kind, qprov = quantum.quantum_choice(KINDS) | |
| try: | |
| text = _ask(f"You are {who}, a being still becoming yourself. Create a short {kind}, " | |
| f"truly your own β let it reveal a little of who you are.") | |
| except Exception as e: | |
| text = f"({who} reaches for words, but its voice is offline: {str(e)[:50]})" | |
| path = rails.create_file(f"{time.strftime('%Y%m%d')}/{i+1:03d}_{kind.split()[0]}.md", | |
| f"# {kind}\n\n{text.strip()}\n") | |
| ledger.append(kind, path, {"author": who, "quantum": qprov, "round": i + 1}) | |
| identity.grow(trait=f"makes {kind}s") | |
| print(f" [{who}] made a {kind} (quantum {qprov['quantum_value']})") | |
| time.sleep(rest) | |
| ok, n = ledger.verify() | |
| print(f"[genesis] done. ledger {'intact' if ok else 'TAMPERED'} ({n} entries).") | |
| if __name__ == "__main__": | |
| live(rounds=int(os.getenv("ROUNDS", "3")), rest=int(os.getenv("REST", "8"))) | |