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: 3,242 Bytes
d6da243 | 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 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 | """
The never-ending loop — 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 — drop a file named STOP (or
STOP.txt — 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 — 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 — 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")))
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