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jilwang804/M-DESIGN-Knowledge-Base

M-DESIGN Knowledge Base and Model Artifacts This dataset contains the released SQLite model-performance databases and model artifacts used by M-DESIGN, the method from "Beyond Model Base Retrieval: Weaving Knowledge to Master Fine-grained Neural Network Design". Contents Each .db file has a model_records table. The first six columns encode fine-grained neural design choices and the final two columns store the measured score and standard deviation. Each… See the full description on the dataset page: https://huggingface.co/datasets/jilwang804/M-DESIGN-Knowledge-Base.

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M-DESIGN Knowledge Base and Model Artifacts

This dataset contains the released SQLite model-performance databases and model artifacts used by M-DESIGN, the method from "Beyond Model Base Retrieval: Weaving Knowledge to Master Fine-grained Neural Network Design".

Contents

Each .db file has a model_records table. The first six columns encode fine-grained neural design choices and the final two columns store the measured score and standard deviation. Each task/dataset directory includes the released PyTorch artifacts: ecc_predictor.pt and model_graph.pt.

Task layout:

  • —node/: node classification model records.
  • —link/: link prediction model records.
  • —graph/: graph classification model records.

Suggested Use

Place the downloaded folder at data/knowledge_base inside the M-DESIGN code repository, then run:

bash
mdesign inspect-kb --task node_classification
mdesign recommend --dataset Cora --task node_classification --max-iter 30

Notes

The databases are released for reproducibility and research use. Baseline logs, temporary trials, ablation outputs, TensorBoard events, private keys, and local machine paths are not part of this release bundle.