Operational (MEASURED laptop-Blackwell)

STATUS: tests PASS. get_kernel import-LIVE. Unsloth/LoRA is the wrong tool. Receipted kernels, not silent CUDA.

Thing Label Method / N / date / what-NOT
tests (PYTHONPATH=torch-ext) PASS MEASURED 2026-08-29T15:54:08Z host betterwithage Windows-10-10.0.26200-SP0. torch 2.10.0+cu128. GPU NVIDIA GeForce RTX 5050 Laptop GPU arch Blackwell. pytest 25 passed, 1 skipped in 0.33s. Failed nodes: none. What-NOT: not a leaderboard. torch.compile fullgraph failures on Windows Blackwell (cl is not found) are MEASURED, not hidden.
Kernel Hub get_kernel import-LIVE kernels 0.16.1. Default: get_kernel("SZLHOLDINGS/YARQA-ATTN", revision="main", trust_remote_code=True)True. backend="cpu"True. trust_remote_code=False → ValueError (SZLHOLDINGS is not a trusted publisher). repo_type=kernel required (kernels 0.16). What-NOT: not a weight load; do not pickle/joblib.load.
formula-tax ADVISORY locked-8 F1 F4 F7 F11 F12 F18 F19 F22. registry_count=21. Λ geomean 1.0. uniqueness Conjecture 1 (never a theorem).
I1–I8 catalog I1 receipt-chain-continuity; I2 ledger-failure-shape; I3 served-run-has-model; I4 signed-columns-atomic; I5 loop-steps-positive; I6 receipt-ed25519-verify; I7 receipt-columns-consistent; I8 flywheel-lineage. Executed by SZLHOLDINGS/szl-invariants. Statuses never coerced. Λ untouched.
CUDA speedup / tokens/s / joules UNAVAILABLE Not claimed. Receipted kernels, not silent CUDA.

GitHub source: szl-holdings/YARQA-ATTN @ 160640bd8ed138e0170838c5a0de470ba8539367. Artifacts: BENCH.laptop-blackwell.json, OPERATIONAL.json.

from kernels import get_kernel
k = get_kernel("SZLHOLDINGS/YARQA-ATTN", revision="main", trust_remote_code=True)

YARQA-ATTN

Status

STATUS: import-LIVE on CPU Kernel Hub get_kernel (kernels 0.16.1). GPU cubins UNAVAILABLE this session (not ROADMAP).

Thing Label Method / N / date / what-NOT
Kernel Hub get_kernel import-LIVE MEASURED 2026-08-28 3:08pm ET on kernels 0.16.1. Package HEAD 7e533ce (7e533ce702029061bc68f9f9cafe88efdd7f5f00). README at MEASURE 2871b3c. Legal name yarqa-attn (Python module yarqa_attn). Variants: build/torch-universal (default get_kernel) and build/torch-cpu (backend="cpu"). Working calls: get_kernel("SZLHOLDINGS/YARQA-ATTN", revision="main", trust_remote_code=True) and the same with backend="cpu". selfcheck ok. max_abs_vs_compartment_ref=3.58e-07 (full 3.5762786865234375e-07), path=torch_compartment. What-NOT: no tokens/s; no joules; not a fourth Flash / Flex / paged stack. Lambda = Conjecture 1 (advisory).
GPU cubins UNAVAILABLE MEASURED 2026-08-28 7:01pm ET this session. Host cursor (Linux 6.12.94+ x86_64, Intel Xeon 8-core). torch 2.13.0+cu130 compiled CUDA 13.0. torch.cuda.is_available()=false. nvidia-smi UNAVAILABLE. device_count=0. Triton 3.7.1 present with no CUDA device. No cubin shipped. No tokens/s. No joules. CPU import-LIVE unchanged. Not a fourth Flash / Flex / paged stack. Lab stays Khipu.

KERNEL kernel card. Original SZL compartment / plug-flow attention cut. Receipt-aware. Honesty-labeled.

Not a Fall 2026 ATELIER weight. No tensors in this repo. Not an alias of szl-receipt-attn. Not a pointer at the Triton trio (szl-receipt-attn, szl-maskmod, szl-block-kv). Those three stay separate. a11oy-net does not list this as a fourth Flash / Flex / paged stack.

GitHub is source of truth: szl-holdings/YARQA-ATTN. KERNEL binds Hub bytes from that tree. Do not PUT an empty card.

Owner KERNEL
Artifact kernel (Python present; no weights; GPU cubins not claimed)
Status import-LIVE CPU · GPU cubins UNAVAILABLE
License Apache-2.0
Λ Conjecture 1 (advisory, never a theorem)
Path torch_compartment (CPU)
Serve studio not this repo. Live CPU lab is szl-model-inference-lab (Khipu GGUF only)

Silhouette: partition a sequence into canals (contiguous compartments), attend within a canal, emit SHA3-256 of the partition and of the attention output. We do not copy Dao hopper, Sage csrc, vLLM paged .cu, cuDNN FMHA, TRT cubins, CuTeDSL, or flex_attention.py. Metaphor only vs szl-holdings/yarqa (CFD; different product). Throughput is MEASURED only from a timed run on named hardware. Until then every speed claim is unstamped. No tokens/s. No joules.

Do not list this next to Chaski, Qantu, Waman, Chakana, or Tinku.

Load

from kernels import get_kernel
attn = get_kernel("SZLHOLDINGS/YARQA-ATTN", revision="main", trust_remote_code=True)

Fashion GO 2026-08-28 3:10pm ET. import-LIVE CPU stays. GPU cubins stamped UNAVAILABLE 2026-08-28 7:01pm ET (no CUDA device this session). Not a fourth Flash / Flex / paged stack.

Apache-2.0. Copyright 2026 SZL Holdings.

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