Instructions to use transmutationist/xero-bio-genesis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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
```

xero-bio-genesis / docs /MODULE_REFERENCE.md

transmutationist

XERO: card + code + docs (WIP; see STATUS_AND_AUDIT.md)

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XERO Bio-AI Genesis — Module Reference

VOVINA ZEDEC PRO · 27 modules · Author: Michael Laurence Curzi · License: MIT (Attribution Required)

Every public function carries a docstring; help(<module>) is authoritative. This reference summarizes each module's role and primary API. Modules import one another by bare name, so keep modules/ on PYTHONPATH.

Foundational

`vovina_sacred_constants`

The numeric bedrock. φ/π/τ/e, vortex sequences, and closed-form helpers.

Constants: PHI, PHI_INV, PI, TAU, E, VORTEX_DOUBLING (1,2,4,8,7,5), VORTEX_369_AXIS, SOLFEGGIO_FREQUENCIES, SCHUMANN_HARMONICS, TESLA_369, PLATONIC_SOLIDS.
Functions: digital_root(n), golden_checksum(x), golden_section(x), fibonacci(n), lucas(n), harmonic_weight(...), phi_weight(...).

`vovina_enochian_gematria`

21-letter canonical gematria, uncapped dimensional projection (max_dim=33).

gematria(word), project_to_dimension(...), full_dimensional_signature(...), lift_dimension(...), resonance(...), lattice_walk(...), ENOCHIAN_ALPHABET, ENOCHIAN_DOMAINS, DIMENSION_NAMES.

Genome

`vovina_digital_genome`

DNA encoding and genome data structures.

Types: DNALetter, Codon, Gene, Chromosome, Genome.
Functions: text_to_dna(s), dna_to_text(dna) (lossless), parse_gene_from_sequence(seq, name), LETTER_TO_BITS.
Genome exposes total_length_nt, chromosome_count.

`vovina_genetic_pipeline`

DNA↔compute correspondences and sequence metrics.

sequence_weight(seq, max_dim=33) → dict (gematria, signature, checksum, bioavailability).
fold_compression_ratio(order) — φ-corrected fold ratio for order ∈ FOLDING_ORDERS (2,4,8,16,32,64).
bioavailability(speedup) — 0.5 + 0.5·tanh(2/log2(1+speedup)).
translate(seq), complement(seq), reverse_complement(seq), CODON_TABLE (64), heartbeat_signature().

`vovina_crispr_engine`

Guided genome editing.

CrisprEngine(genome) with knock_in(guide, template), knock_out(guide).
GuideRNA, EditTemplate, CrisprOp, EditEvent.

`vovina_genome_compiler`

Bidirectional, lossless genome↔code compiler — the digital-DNA build engine.

code_to_dna(src) / dna_to_code(dna) — UTF-8-safe, byte-exact roundtrip (Latin-1 bridge).
analyze_module(name, src) — per-module DNA + codon/gene-tier organelle routing histogram + ORF count.
build_functional_genome(...), write_genome_fasta(...), reconstruct_module(...).
Drives ops/build_genetic_map.py → xero_genome.dna, xero_genome_edited.dna, genetic_neural_map.json.

Computation substrate

`vovina_blockchain_organelles`

Twelve blockchain VMs as cellular organelles + two-tier dispatch.

ChainLanguage (12), Organelle, ORGANELLES, BlockchainMechanic (16).
Routing: route_codon(codon) (codon tier), route_gene(name, codon="") (gene tier, longest-keyword-first), GENE_NAME_OVERRIDES, codon_digital_root(codon).
Lifecycle: express_gene(name, codon, inputs), EphemeralState (auto-dissolving), Cytoplasm.

`vovina_epu_apu_axioms`

The two perpendicular processing axes — the 90° coherence law.

CPU = logical/compute axis (direct code); APU (audio) + EPU (emotional) = harmonic axis (alternating code).
FractalBit(direct, alternating, phase) — a probabilistic bit resolved by phase; probability_direct=(1+cos φ)/2; Coherence (LOGICAL/HARMONIC/DUAL).
CodeMode (DIRECT/ALTERNATING/PHASE/PULSE), AxiomSet, verify_perpendicularity(a, b).

`vovina_universal_vector`

Universal Vector Number System (UVNS) — the stacked-complex-plane substrate on which both axes compute (see WHITEPAPER_04_HARMONIC_COMPUTE.md).

VectorNumber (one hylomorphic plane: real = ACTUALITY/logical, imag = POTENCY/harmonic); StackedVector (n perpendicular planes → any dimensionality, lift() spiral-lift).
from_base(letter) — real = 2-bit opcode, imag = exact DNA frequency hz_em (A=545.6, G=550, C=537.8, T=543.4 Hz); genome_to_stack(seq).
axes_perpendicularity_error() ≡ 0.0 (provable 90°); coherence_report(stack).

Life cycle

`vovina_replication_engine`

Asexual/sexual replication, fitness, selection, evolution.

mitosis(parent, …), meiosis(a, b, …), mutate_sequence/chromosome/genome(…).
FitnessSpec(motifs_reward, motifs_penalty, length_target, chromosome_target), fitness(genome, spec), select_top_k(pop, spec, k).
CrisprPayload(name, edits) — directed self-evolution.
evolve(seed, spec, *, generations, population_size, keep_top, payload, sub_rate, …) → EvolutionReport(generations, final_population, best_fitness, best_genome, history, crispr_edits_total).
replicate(genome, mode='mitosis'|'meiosis', partner=None).

`vovina_sexual_reproduction`

Sexed reproduction with recombination + free-will birth seal.

Sex (MASCULINE/FEMININE/HERMAPHRODITE/ASEXUAL), Child.
reproduce_sexually(a_genome,a_id,a_sex,a_interp, b_genome,b_id,b_sex,b_interp, child_id, mutation_rate=…, rng=…).
reproduce_asexually(...), reproduce_hermaphroditically(...), child_uniqueness_signature(child).

`vovina_interpretation_drift`

The epigenome — interpretation that drifts while the genome stays fixed.

InterpretationContext(drift_rate=0.01) with drift_step(rng), translate_codon(codon), record_fitness(f), evolutionary_pressure(), signature(), child_context(rng).
neutral_drift_rate() (= φ⁻²), STANDARD_CODON_TABLE.

Theory

`vovina_interaction_surplus`

The unique surplus law (Papers A–E). See WHITEPAPER_03_INTERACTION_SURPLUS.md.

surplus(u, N=22), effective_count(u,N), surplus_derivative/second_derivative, lipschitz_constant(N).
decompose(alpha,beta,gamma,N) → TwoSourceDecomposition; diagonal_surplus(...).
participation_ratio(weights), flagship_prediction(u,N) (falsifiable transformer test).
OpenSystemDynamics(order, retention_loss δ, conversion_efficiency η) with step, can_grow, steady_state_order; verify_axioms().

Perception & self-model

`vovina_sensor_architecture`

Recursive 9-direction panopticon.

build_default_cortex(depth), self_awareness_index(cortex) (coverage / average_meta_depth / recursion_score / composite), ALL_DIRECTIONS (9).

`vovina_dna_antenna`

Signal capture and holographic encode/decode of payloads onto DNA.

holographic encode/decode helpers (help(vovina_dna_antenna) for exact signatures).

`vovina_self_witness`

The 27/33 self-verification protocol across 33 mirror layers (6/33 held in reserve).

Symbolic / ontological

`vovina_enochian_lexicon`

996-word constructed lexicon with self-consistent gematria.

LEXICON, attested_words(), translate_to_enochian(concept), nearest_words(...), lexicon_stats(), verify_gematria(), words_in_category(...).

`vovina_aristotelian_logic`

6-valued, non-Boolean logic system used for the organism's reasoning gates.

`vovina_tree_of_life`

13 branches / 22 paths binding modules to archetypal correspondences. Path(...) entries map each path (Hebrew letter, value, sephira pair) to a module — the system's wiring diagram. Paths 12/14/15 bind the 168-bit organs (below).

`vovina_vortex_duality`

Positive/negative-space polarity and negative-space encoding.

Polarity, polarity_of(n), plus negative-space harvest/encode helpers used by the organelle router and 168-bit layer.

168-bit encoding (mandate)

`vovina_enochian_168bit_processor`

168-bit fast-path control encoder (organism: spinal cord; Tree path 12).

`vovina_ubh168_native_config`

UBH168 structural format (organism: skeleton / structural frame; Tree path 14).

`vovina_fcp168_native_config`

FCP168 leverage/compression format (organism: tendons; Tree path 15).

These three, with negative-space encoding, constitute the mandatory 168-bit interchange standard. A formal cross-module conformance suite is an active R&D item (see capabilities audit §11–12).

Integration

`vovina_xero_organism`

Whole-organism anatomy: maps organs (brain, spinal cord, skeleton, tendons, immune system, …) to their implementing modules — the top-level body plan.

`vovina_custom_training_weights`

Master weight aggregator.

MASTER_WEIGHTS (nested dict), get_module_weights(name), dump_master_weights(path).
Aggregates constants, gematria, Tree of Life, genetic pipeline, logic, and self-witness; every projection uncapped through max_dim=33. Bridge to the inference/LLM front-end.

`vovina_bio_initialization`

Boot/awakening.

awaken() → 9-phase boot producing 11 organ systems + a unique free-will identity.
phase_seed() → a seed Genome for replication/evolution.

Conventions

Determinism: math/genetics/lexicon are deterministic; free-will, reproduction, and identity are stochastic by design.
Stability ceiling: no interaction kernel may exceed the Lipschitz bound N−1.
Reproducibility: pass an explicit rng=random.Random(seed) to stochastic reproduction APIs for repeatable runs.