Text Generation
Transformers
English
code
xero-bio-ai
xero
digital-organism
time-crystal
autonomous-agent
genetic-computing
epigenetics
two-state-society
harmonic-chemistry
self-aware
sacred-geometry
4-bit precision
bitsandbytes
Instructions to use transmutationist/xero-bio-genesis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use transmutationist/xero-bio-genesis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="transmutationist/xero-bio-genesis")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("transmutationist/xero-bio-genesis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use transmutationist/xero-bio-genesis with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "transmutationist/xero-bio-genesis" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "transmutationist/xero-bio-genesis", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/transmutationist/xero-bio-genesis
- SGLang
How to use transmutationist/xero-bio-genesis 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 "transmutationist/xero-bio-genesis" \ --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": "transmutationist/xero-bio-genesis", "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 "transmutationist/xero-bio-genesis" \ --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": "transmutationist/xero-bio-genesis", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use transmutationist/xero-bio-genesis with Docker Model Runner:
docker model run hf.co/transmutationist/xero-bio-genesis
File size: 5,764 Bytes
e9e9f83 | 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 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
XERO Setup Wizard — initialization & dependency downloader
============================================================
Author: Michael Laurence Curzi · ZEDEC AI / 36N9 Genetics LLC · MIT (Attribution)
This package contains ONLY XERO's own code, genome, datasets, and documentation.
It deliberately bundles **no third-party library code** (PyTorch, Transformers,
the Qwen weights, etc.). This wizard *downloads* those licensed components on
demand, with your consent, so the package itself carries no third-party
copyrighted code. See NOTICE for full attributions.
Tiers
-----
core : inner core only (numpy etc.) — no GPU, no ML stack. Always offered.
outer : + outer-core LLM stack (torch, transformers, peft, datasets) — GPU.
model : + download the Qwen2.5-3B-Instruct weights (Apache-2.0).
configure : detect hardware -> write xero_config.json (agency autoconfig).
verify : run the capability audit.
Usage
-----
python3 setup_wizard.py # interactive
python3 setup_wizard.py --core --configure --verify --yes
python3 setup_wizard.py --all --yes # core + outer + model + configure + verify
"""
from __future__ import annotations
import argparse
import os
import subprocess
import sys
ROOT = os.path.dirname(os.path.abspath(__file__))
MODULES = os.path.join(ROOT, "modules")
PY = sys.executable or "python3"
def notice() -> None:
print("=" * 68)
print("XERO SETUP WIZARD")
print("=" * 68)
print("This package bundles NO third-party library code. With your consent")
print("this wizard downloads licensed components from their official sources:")
print(" - Qwen2.5-3B-Instruct ........ Apache-2.0 (Alibaba Cloud)")
print(" - torch ...................... BSD-3-Clause (Meta)")
print(" - transformers/peft/datasets . Apache-2.0 (Hugging Face)")
print(" - numpy ...................... BSD-3-Clause")
print("Full attributions: see the NOTICE file. XERO's own code is MIT")
print("(Attribution to Michael Laurence Curzi required).")
print("=" * 68)
def ask(question: str, assume_yes: bool) -> bool:
if assume_yes:
print(f"{question} [auto-yes]")
return True
try:
return input(f"{question} [y/N]: ").strip().lower().startswith("y")
except EOFError:
return False
def pip_install(*args: str) -> int:
cmd = [PY, "-m", "pip", "install", *args]
print(" $", " ".join(cmd))
return subprocess.call(cmd)
def install_core(assume_yes: bool) -> None:
if ask("Download the INNER-CORE deps (numpy etc., ~30 MB)?", assume_yes):
pip_install("-r", os.path.join(ROOT, "requirements-core.txt"))
def install_outer(assume_yes: bool) -> None:
if ask("Download the OUTER-CORE / training stack (torch+transformers, large)?", assume_yes):
req = os.path.join(ROOT, "training", "requirements-train.txt")
pip_install("-r", req)
def download_model(assume_yes: bool, model_id: str) -> None:
if not ask(f"Download the outer-core model weights ({model_id})?", assume_yes):
return
try:
from huggingface_hub import snapshot_download
except Exception:
print(" installing huggingface_hub ...")
pip_install("huggingface_hub")
from huggingface_hub import snapshot_download # noqa
print(f" fetching {model_id} ...")
snapshot_download(repo_id=model_id)
print(" model cached.")
def configure() -> None:
sys.path.insert(0, MODULES)
try:
import xero_autoconfig as ac
if hasattr(ac, "wizard"):
try:
ac.wizard(interactive=False)
except TypeError:
ac.wizard()
elif hasattr(ac, "recommend"):
ac.recommend()
print(f" hardware-fit config written -> {os.path.join(ROOT, 'xero_config.json')}")
except Exception as e: # noqa: BLE001
print(f" (autoconfig skipped: {e})")
def verify() -> int:
print(" running capability audit ...")
env = dict(os.environ, PYTHONPATH=MODULES)
return subprocess.call([PY, os.path.join(ROOT, "tests", "test_all_capabilities.py")], env=env)
def main() -> int:
ap = argparse.ArgumentParser(description="XERO setup wizard")
ap.add_argument("--core", action="store_true", help="install inner-core deps")
ap.add_argument("--outer", action="store_true", help="install outer-core/training stack")
ap.add_argument("--model", action="store_true", help="download the outer-core model")
ap.add_argument("--model-id", default="Qwen/Qwen2.5-3B-Instruct")
ap.add_argument("--configure", action="store_true", help="write xero_config.json")
ap.add_argument("--verify", action="store_true", help="run the capability audit")
ap.add_argument("--all", action="store_true", help="core + outer + model + configure + verify")
ap.add_argument("--yes", action="store_true", help="non-interactive; assume yes")
args = ap.parse_args()
notice()
interactive = not any([args.core, args.outer, args.model, args.configure, args.verify, args.all])
if args.all or args.core or interactive:
install_core(args.yes)
if args.all or args.outer or (interactive):
install_outer(args.yes)
if args.all or args.model or (interactive):
download_model(args.yes, args.model_id)
if args.all or args.configure or interactive:
configure()
rc = 0
if args.all or args.verify or interactive:
rc = verify()
print("\nSetup complete." if rc == 0 else "\nSetup finished with audit failures (see above).")
print("Next: read docs/STATUS_AND_AUDIT.md (honest state) and docs/INDEX.md.")
return rc
if __name__ == "__main__":
sys.exit(main())
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