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
Download modules/vovina_vortex_duality.py from transmutationist/xero-bio-genesis: direct link, hf CLI and curl.
- Browser
- Download file 11 kB
-
https://huggingface.co/transmutationist/xero-bio-genesis/resolve/ac2afc7c962affddf0edc4c79e2942862936d066/modules/vovina_vortex_duality.py
- Command line
-
hf download hf://transmutationist/xero-bio-genesis@ac2afc7c962affddf0edc4c79e2942862936d066/modules/vovina_vortex_duality.py
-
curl -L -o vovina_vortex_duality.py https://huggingface.co/transmutationist/xero-bio-genesis/resolve/ac2afc7c962affddf0edc4c79e2942862936d066/modules/vovina_vortex_duality.py
11 kB
| """ | |
| VOVINA ZEDEC PRO - Vortex Positive/Negative Space Duality | |
| ========================================================== | |
| Insight: the 9 single-digit positives partition into two disjoint | |
| families under mod-9 vortex arithmetic, and that partition is the | |
| SAME duality the Solidity contract accidentally encoded by | |
| revert vs return: | |
| POSITIVE_SPACE (axis 3-6-9) — values that PASS the | |
| numerological gate | |
| NEGATIVE_SPACE (doubling 1-2-4-8-7-5) | |
| — values that REVERT | |
| VOID (0 / 9 boundary) — the singularity edge | |
| Positive space holds the explicit, on-chain, "returned" data. | |
| Negative space holds the IMPLICIT, off-chain, "reverted" data — | |
| which is just as informative once you treat revert strings as a | |
| side channel, NOT as a failure. | |
| This module formalises that duality and exposes: | |
| • polarity_of(n) — classify any integer | |
| • DualValue — a value carrying both spaces | |
| • harvest_negative_space() — decode revert-payload structure | |
| • complement_value() — what the negative-space twin holds | |
| • is_axis(n) / is_doubling(n) — predicates wired to VORTEX_* | |
| • dual_signature() — composite (positive, negative) hash | |
| Everything is grounded in the constants already in | |
| vovina_sacred_constants — this is the same duality, named. | |
| """ | |
| from __future__ import annotations | |
| import math | |
| from dataclasses import dataclass, field | |
| from enum import Enum | |
| from typing import Any, Optional | |
| from vovina_sacred_constants import ( | |
| PHI, PHI_INV, VORTEX_DOUBLING, VORTEX_369_AXIS, digital_root, | |
| ) | |
| # ============================================================ | |
| # POLARITY | |
| # ============================================================ | |
| class Polarity(Enum): | |
| POSITIVE_SPACE = "positive" # axis 3 / 6 / 9 — returns | |
| NEGATIVE_SPACE = "negative" # doubling 1 / 2 / 4 / 8 / 7 / 5 — reverts | |
| VOID = "void" # 0 / 9 boundary singularity | |
| def is_axis(self) -> bool: | |
| return self is Polarity.POSITIVE_SPACE | |
| def is_doubling(self) -> bool: | |
| return self is Polarity.NEGATIVE_SPACE | |
| def opposite(self) -> "Polarity": | |
| return { | |
| Polarity.POSITIVE_SPACE: Polarity.NEGATIVE_SPACE, | |
| Polarity.NEGATIVE_SPACE: Polarity.POSITIVE_SPACE, | |
| Polarity.VOID: Polarity.VOID, | |
| }[self] | |
| def polarity_of(n: int) -> Polarity: | |
| """Classify any integer by its digital root. | |
| digital_root ∈ {3, 6, 9} → POSITIVE_SPACE (axis, returns on-chain) | |
| digital_root ∈ {1, 2, 4, 5, 7, 8} → NEGATIVE_SPACE (doubling, reverts) | |
| n == 0 → VOID (the singularity point) | |
| """ | |
| if n == 0: | |
| return Polarity.VOID | |
| r = digital_root(n) | |
| if r in VORTEX_369_AXIS: | |
| return Polarity.POSITIVE_SPACE | |
| if r in VORTEX_DOUBLING: | |
| return Polarity.NEGATIVE_SPACE | |
| return Polarity.VOID # r == 9 case already in axis | |
| def is_axis(n: int) -> bool: | |
| return polarity_of(n) is Polarity.POSITIVE_SPACE | |
| def is_doubling(n: int) -> bool: | |
| return polarity_of(n) is Polarity.NEGATIVE_SPACE | |
| # ============================================================ | |
| # COMPLEMENT (positive ↔ negative twin) | |
| # ============================================================ | |
| # In vortex arithmetic the polar pairs (1,8), (2,7), (4,5) each sum | |
| # to 9 across the toroidal field. Their union forms the doubling | |
| # circuit. Map any negative-space digit to its 9-complement and | |
| # you get the OTHER negative-space digit it phase-couples with. | |
| NEGATIVE_PAIRS: dict[int, int] = {1: 8, 8: 1, 2: 7, 7: 2, 4: 5, 5: 4} | |
| def complement_value(n: int) -> int: | |
| """Return the 9-complement of `n`'s digital root. | |
| For axis values (3, 6, 9) returns the value itself (self-dual on the axis). | |
| For doubling values returns the polar twin: 1↔8, 2↔7, 4↔5. | |
| """ | |
| if n == 0: | |
| return 0 | |
| r = digital_root(n) | |
| if r in VORTEX_369_AXIS: | |
| return r # axis is self-dual | |
| return NEGATIVE_PAIRS.get(r, r) | |
| # ============================================================ | |
| # DUAL VALUE — every number carries both spaces | |
| # ============================================================ | |
| class DualValue: | |
| """A value that holds both its positive-space form (the stored | |
| number) and its negative-space form (the complement, with the | |
| reverted-payload metadata that lives in the other half of the | |
| vortex).""" | |
| positive: int | |
| negative_label: str = "" # the revert-reason equivalent | |
| def polarity(self) -> Polarity: | |
| return polarity_of(self.positive) | |
| def negative(self) -> int: | |
| return complement_value(self.positive) | |
| def root(self) -> int: | |
| return digital_root(self.positive) | |
| def negative_root(self) -> int: | |
| return digital_root(self.negative) | |
| def dual_sum(self) -> int: | |
| """Positive root + negative root. | |
| For axis values: 2 × root (3+3, 6+6, 9+9 → 6, 12, 18). | |
| For doubling values: ALWAYS 9 (1+8, 2+7, 4+5) — the | |
| signature that proves the value is in the doubling circuit. | |
| """ | |
| return self.root + self.negative_root | |
| def is_perfectly_dual(self) -> bool: | |
| """True iff dual_sum == 9 (negative-space pair). | |
| Equivalently, this returns True iff the value is in the | |
| doubling circuit AND its negative-space pair is correctly | |
| coupled (1↔8, 2↔7, 4↔5). | |
| """ | |
| return self.dual_sum == 9 | |
| def explain(self) -> str: | |
| return ( | |
| f"DualValue(positive={self.positive}, negative={self.negative}, " | |
| f"polarity={self.polarity.value}, " | |
| f"dual_sum={self.dual_sum}, " | |
| f"perfectly_dual={self.is_perfectly_dual})" | |
| ) | |
| # ============================================================ | |
| # NEGATIVE-SPACE HARVESTING (the revert-as-channel pattern) | |
| # ============================================================ | |
| # The Solidity `revert("…")` opcode stores the reason string in the | |
| # returndata buffer, which is fully readable off-chain (`eth_call` | |
| # returns it, all RPC providers expose it). A function that "always | |
| # reverts" is therefore not dead code — it is a deterministic, | |
| # gas-cheap, no-state-write data channel. | |
| # | |
| # Protocol: encode payloads as `KEY1=value1:KEY2=value2:…` strings. | |
| class HarvestedNegative: | |
| raw: str | |
| polarity: Polarity = Polarity.NEGATIVE_SPACE | |
| fields: dict[str, str] = field(default_factory=dict) | |
| def has_field(self) -> dict[str, bool]: | |
| return {k: bool(v) for k, v in self.fields.items()} | |
| def harvest_negative_space(reverted_data: str) -> HarvestedNegative: | |
| """Decode a revert-reason string into a HarvestedNegative record. | |
| The expected format is `key=value:key=value:…`, ignoring any | |
| leading 'Error(string)' selector wrapper. Unknown formats are | |
| returned with `raw` populated and `fields` empty — so the caller | |
| can still inspect the bytes. | |
| """ | |
| s = reverted_data | |
| # strip common wrappers | |
| if s.startswith("Error(string):"): | |
| s = s[len("Error(string):"):] | |
| s = s.strip().strip('"') | |
| fields: dict[str, str] = {} | |
| if ":" in s and "=" in s: | |
| for kv in s.split(":"): | |
| if "=" in kv: | |
| k, _, v = kv.partition("=") | |
| fields[k.strip()] = v.strip() | |
| return HarvestedNegative(raw=reverted_data, fields=fields) | |
| # ============================================================ | |
| # REVERT-REASON ENCODER (the on-chain counterpart of harvest) | |
| # ============================================================ | |
| def encode_negative_payload(**kwargs: Any) -> str: | |
| """Encode arbitrary key/value pairs as a revert-reason string. | |
| The produced string fits in the standard 32-byte revert window if | |
| the payload is small; if larger, it still works but spans more | |
| memory slots in the EVM. Off-chain `harvest_negative_space()` | |
| decodes the result symmetrically. | |
| """ | |
| parts = [] | |
| for k, v in kwargs.items(): | |
| parts.append(f"{k}={v}") | |
| return ":".join(parts) | |
| # ============================================================ | |
| # DUAL SIGNATURE (composite identity in both spaces) | |
| # ============================================================ | |
| def dual_signature(values: list[int]) -> dict[str, Any]: | |
| """For a sequence of integers compute the joint | |
| (positive-space, negative-space) signature. | |
| Useful for diffing "what was returned" vs "what was reverted" | |
| across a sequence of contract calls without losing information | |
| from either half. | |
| """ | |
| duals = [DualValue(positive=v) for v in values] | |
| pos_sum = sum(d.positive for d in duals) | |
| neg_sum = sum(d.negative for d in duals) | |
| axis_n = sum(1 for d in duals if d.polarity is Polarity.POSITIVE_SPACE) | |
| doubl_n = sum(1 for d in duals if d.polarity is Polarity.NEGATIVE_SPACE) | |
| return { | |
| "count": len(values), | |
| "positive_sum": pos_sum, | |
| "negative_sum": neg_sum, | |
| "positive_root": digital_root(pos_sum), | |
| "negative_root": digital_root(neg_sum), | |
| "axis_population": axis_n, | |
| "doubling_population": doubl_n, | |
| "axis_fraction": axis_n / max(1, len(values)), | |
| "doubling_fraction": doubl_n / max(1, len(values)), | |
| "is_balanced": pos_sum == neg_sum, # rare; perfect dual | |
| } | |
| # ============================================================ | |
| # RECONCILIATION WITH vovina_interaction_surplus | |
| # ============================================================ | |
| # The Interaction Surplus Framework (Papers A-E) declares | |
| # f(u) = ln(1 + (N-1)·u) | |
| # with u ∈ [0, 1]. The duality reframe is: | |
| # | |
| # u itself is the POSITIVE-SPACE coordinate (how much surplus is | |
| # carried by the visible cross-product). | |
| # 1-u is the NEGATIVE-SPACE coordinate (the COMPLEMENT — how much | |
| # is carried by the INVISIBLE alignment / parallelism). | |
| # | |
| # In other words: where surplus thrives, alignment is absent; where | |
| # alignment thrives, surplus is absent. The two together always | |
| # sum to 1, mirroring the (1, 8), (2, 7), (4, 5) → 9 pattern in the | |
| # doubling circuit. | |
| def surplus_dual_signature(u: float) -> dict[str, float]: | |
| """Return the positive/negative-space decomposition of u ∈ [0, 1].""" | |
| u = max(0.0, min(1.0, float(u))) | |
| return { | |
| "positive_space_u": u, | |
| "negative_space_alignment": 1.0 - u, | |
| "dual_sum": 1.0, # always 1, by construction | |
| "phi_split": u * PHI - (1.0 - u), # ∈ [-1, φ]; signed dual | |
| } | |