| # Archive: earlier models (reference only) | |
| **Do not use these files with `hybrid_engine/`.** The current model is v2.0 in `hybrid_engine/artifacts/` (see the main README). The models here were trained on different inputs (they use community name and flair, user/post IDs or feed position) and have their own vocabularies and standardisation. They are kept so the results in `REPORT.md` can be checked and compared. | |
| | Folder | What it is | Status | | |
| |---|---|---| | |
| | `engine_v1_1/` | the previous hybrid engine (same design, but its models used community name + flair). ONNX, `meta.json`, reports, `pytorch_checkpoints/` (5 seeds per model) | replaced by v2.0 | | |
| | `phase1_models/` | the first five models (LR, DeepFM, Wide&Deep, DCN V2, SASRec), trained with user/post IDs and feed position. ONNX, checkpoints, metadata, `Model_Explainer.docx`, `example_inference.py` | research baseline | | |
| | `v1_two_stage_engine/` | Stage-2 models of the first two-stage engine (tag match, then model). ONNX, checkpoints, Stage-1 weights and results | research baseline, outperformed | | |
| The engine v1.1 files can be loaded on their own with `HybridRecommender(artifacts_dir="archive/engine_v1_1")`, but that version needs content vectors built with its own text recipe ("title. community. flair. body"), not the v2.0 one. | |