Views
No views yet
.rknot).knot weight format. Drops
non-standing-wave embedding dimensions, signed-quantizes the rest at
amplitude-graded bit widths, and ships the result as a single .rknot
file with a header pointer table for mmap-style block access.| Artifact | Bytes | Ratio vs dense |
|---|---|---|
Dense .knot (Q4_K_M source) | 4,677,147,097 (4.36 GiB) | 1.00× |
Resonance Knot .rknot | 845,659,315 (806.48 MiB) | 5.53× smaller |
k = 0.30 × hidden_dimmagic : 6 bytes "RKNOT\x02"
header_len : 4 bytes u32 LE — JSON header byte length
header_json : N bytes manifest, per-layer pointers, arch metadata
body : rest concatenated quantized blocksRknotLayerRef entries with byte offsets
into the body so a loader can mmap and pull individual blocks
without re-parsing the body.open-source/gnosis/distributed-inference/src/rknot/.
End-to-end probes (load → decode → smoke):1cargo run --release --bin verify-rknot -- \
2 --rknot deepseek-r1-7b.rknot \
3 --dense deepseek-r1-7b.knot \
4 --max-layers 5open-source/gnosis-math/Gnosis/ResonanceKnot*.lean.--input-pca flag of encode-rknot but was not used for this build.forkjoin-ai/distributed-inference Cloud Build
pipeline that fetches the source GGUF from deepseek-ai/DeepSeek-R1-Distill-Qwen-7B, encodes a
dense .knot, then repacks via encode-rknot --apply-fp48. See the
end-to-end yaml for reproducibility:
cloudbuild-llama-70b-end-to-end.yaml.