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Quantizer

Syntologyentry name in harvested coderead from the graph 2026-09-24

Quantizer appears in the code Syntology harvested for 10 papers, as 11 distinct code bodies found in 11 places (a place is one code body under one paper). At least one of them ran in 6 of the papers; 2 of the code bodies carry a behaviour fingerprint.

What this page is not. Routines are grouped here by the exact string of their function or class name. Nothing asserts that two samples named Quantizer do the same thing, share code, or are comparable; the name is a string, not an identity. Behaviour outputs (what a fingerprinted sample returned on the shared battery) are not in this export and are not shown here; the graph at syntology.ai holds them. "Ran" means executed on a synthesized fixture, not that the code is correct or reproduces a paper.

Samples Syntology

Syntology ran 6 of the 11 distinct code bodies named Quantizer; 5 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
0ran · our draft was wrong
0ran · fixture could not drive it
6ran
5unverified
2fingerprinted

Licence is a property of each copy, so it is counted per place: 4 of the 11 places are pointer only (Syntology does not serve that copy's text). This site shows no code text for any sample; every row below links to the file in its repository where the record names one.

“Ran” means the sample executed on a synthesized input; it does not mean the output is correct. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code, and those samples did run. The ran count above is every status except unverified, the same rule as each paper page.

Papers

10 papers shown of 10, newest first; 11 places in the table. A paper with no recorded date is placed by the month its arXiv id encodes, shown in the Date column as YYYY-MM (from id). One row per place: a paper whose repository defines the name more than once appears more than once, and the same code body held for several papers appears once under each, with the same status. Titles and dates are the archive's archive 2025-07-28 for papers in the archive, and the graph's for 3 papers added by Syntology. Status and fingerprint are Syntology's record of each code body; licence is recorded for each place. The File cell ends with the code body's code_sha256, Syntology's identity for that exact code: an agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

PaperDateFileStatus SyntologyLicence
FASQ: Flexible Accelerated Subspace Quantization for Calibration-Free LLM Compression added by Syntology 2026-05 (from id) ist-daslab/gptq/quant.py fc31370a0c6e1aaf unverified Apache-2.0 (permissive)
Democratizing planetary-scale analysis: An ultra-lightweight Earth embedding database for accurate and flexible global land monitoring added by Syntology 2026-01 (from id) shuangchencc/ESD/esd_quantizer.py 57a821bfea62482b ran · metamorphic tier: invariant fingerprinted AGPL-3.0 (copyleft) · pointer only
FACE: A General Framework for Mapping Collaborative Filtering Embeddings into LLM Tokens added by Syntology 2025-10 (from id) YixinRoll/FACE/encoder/FACE.py b5e02485fef7fc11 unverified no licence file found · pointer only
AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration 1 Jun 2023 xvyaward/qeft/qeft/quant.py 5608d56b0c71e653 ran · metamorphic tier: deterministic MIT (permissive)
A Vector Quantized Approach for Text to Speech Synthesis on Real-World Spontaneous Speech 8 Feb 2023 b04901014/mqtts/quantizer/models.py 4cfba0adf1107c8e ran MIT (permissive)
GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers 31 Oct 2022 cornell-zhang/llm-datatypes/neural_compressor/torch/algorithms/weight_only/gptq.py dd6638bb4690fc4c unverified Apache-2.0 (permissive)
GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers 31 Oct 2022 huggingface/text-generation-inference/server/text_generation_server/layers/gptq/quantize.py 7452671bd2402cf2 unverified Apache-2.0 (permissive)
OPT: Open Pre-trained Transformer Language Models 2 May 2022 xvyaward/owq/owq/quant.py 352d10b844458470 unverified no licence file found · pointer only
Mixed-Precision Neural Network Quantization via Learned Layer-wise Importance 16 Mar 2022 1hunters/LIMPQ/quantization_training/quan/quantizer/lsq.py c72e6780cb69622d ran · metamorphic tier: deterministic MIT (permissive)
Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes 26 Oct 2021 secure-ai-systems-group/qu-anti-zation/attack_w_lossfn.py d70c915efcf4d1a4 ran MIT (permissive)
Neural Discrete Representation Learning 2 Nov 2017 explainingai-code/VQVAE-Pytorch/model/vqvae.py 61f7701b94565897 ran fingerprinted no licence file found · pointer only

This site shows no code text; each File cell links to the file on GitHub at the repository's current default branch, which may have changed since the harvest. "Pointer only" means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence cell for the reason. Per-sample records for a paper are on its paper page under "Code Syntology ran".

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections