Home › Code › write_model

write_model

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

write_model appears in the code Syntology harvested for 15 papers, as 11 distinct code bodies found in 17 places (a place is one code body under one paper). At least one of them ran in 0 of the papers; 0 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 write_model 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 0 of the 11 distinct code bodies named write_model; 11 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
0ran
11unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 9 of the 17 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

15 papers shown of 15, newest first; 17 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; 1 papers have no page here and are shown by arXiv id only. 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
ResMoE: Space-efficient Compression of Mixture of Experts LLMs via Residual Restoration 10 Mar 2025 idea-isail-lab-uiuc/resmoe/mixtral/resmoe_mixtral/convert_mixtral_weights_to_hf.py ee2001e1c7496dc4 unverified MIT (permissive)
CodeJudge: Evaluating Code Generation with Large Language Models 3 Oct 2024 VichyTong/CodeJudge/evaluation/model/convert_llama_weights_to_hf.py 5f56e1f4e5b6ba8c unverified Apache-2.0 (permissive)
HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection 26 Sep 2024 deeplearning-wisc/haloscope/llama_iti/convert_llama_weights_to_hf.py 4681d3d61616d9e0 unverified no licence file found · pointer only
SEED: Accelerating Reasoning Tree Construction via Scheduled Speculative Decoding 26 Jun 2024 Linking-ai/SEED/src/llama_tree_attn/convert_llama_weights_to_hf.py 731285361b7dea0e unverified no licence file found · pointer only
LoCoCo: Dropping In Convolutions for Long Context Compression 8 Jun 2024 VITA-Group/LoCoCo/llama/convert_llama_weights_to_hf.py b91ba72f3b013e76 unverified no licence file found · pointer only
Adaptive Image Quality Assessment via Teaching Large Multimodal Model to Compare 29 May 2024 Q-Future/Compare2Score/q_align/model/convert_mplug_owl2_weight_to_hf.py c40b2d63fc02cac4 unverified MIT (permissive)
MeteoRA: Multiple-tasks Embedded LoRA for Large Language Models 19 May 2024 paragonlight/meteor-of-lora/base_model/llama/convert_llama_meteor_weights_to_hf.py b91ba72f3b013e76 unverified no licence file found · pointer only
Okay, Let's Do This! Modeling Event Coreference with Generated Rationales and Knowledge Distillation 4 Apr 2024 csu-signal/llama_cdcr/convert_llama_weights_to_hf.py 4b597d1b6e00be58 unverified no licence file found · pointer only
How Large Language Models Encode Context Knowledge? A Layer-Wise Probing Study 25 Feb 2024 jometeorie/probing_llama/code/llama/convert_llama_weights_to_hf.py 731285361b7dea0e unverified no licence file found · pointer only
How Large Language Models Encode Context Knowledge? A Layer-Wise Probing Study 25 Feb 2024 jometeorie/probing_llama/code/custom_llama/convert_llama_weights_to_hf.py cfeea96bf995824a unverified no licence file found · pointer only
Style Vectors for Steering Generative Large Language Model 2 Feb 2024 dlr-sc/style-vectors-for-steering-llms/utils/convert_llama_weights_to_hf.py cfeea96bf995824a unverified MIT (permissive)
Multi-Candidate Speculative Decoding 12 Jan 2024 njunlp/mcsd/MCSD/model/llama_tree_attn/convert_llama_weights_to_hf.py 731285361b7dea0e unverified MIT (permissive)
LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models 30 Aug 2023 Glaciohound/LM-Infinite/models/get_llama2/convert_llama_weights_to_hf.py 25ab7cdc2eb3c237 unverified MIT (permissive)
Do Emergent Abilities Exist in Quantized Large Language Models: An Empirical Study 16 Jul 2023 rucaibox/quantizedempirical/convert_llama_weights_to_hf.py 25ab7cdc2eb3c237 unverified no licence file found · pointer only
Do Emergent Abilities Exist in Quantized Large Language Models: An Empirical Study 16 Jul 2023 rucaibox/quantizedempirical/models/convert_llama_weights_to_hf.py 57f5bf024e9e6eb0 unverified no licence file found · pointer only
Exploring Self-supervised Logic-enhanced Training for Large Language Models 23 May 2023 sparkjiao/logicllm/convert_llama_weights_to_hf.py de4478ea1dfdf42d unverified MIT (permissive)
arXiv:2025.findings-emnlp.435 nguyenngocbaocmt02/OT-Intervention/lofit_models/convert_llama_weights_to_hf.py 25ab7cdc2eb3c237 unverified MIT (permissive)

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