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AM13_MeltpoolNet

Process parameters + material composition -> melt-pool outcome: 5-way mode (T-AM2) and depth/width/length geometry in um (T-AM1). Tabular. Category C, task T-AM2 + T-AM1, in the unified Smart-Manufacturing SFT schema.

Records

3,019 records (train=3,019). Model input: tabular — no image.

Unified SFT schema (7 fields)

field type meaning
query str the question / instruction (model input)
image Image | null the INPUT image (bytes embedded) — null for tabular records
annot str the answer — for this dataset: mode: a class label (text, one of keyhole/LOF/balling/desirable/spatter formation); geometry: a JSON object of depth/width/length in um
reasoning null no native CoT in this dataset
cate "C" SFT category
task "T-AM2 + T-AM1" unified task id
metadata str (JSON) split, provenance, units, input, license, and (for AM11/13) taxonomy_note

Notes

Leakage-guarded by an INPUT ALLOWLIST — meltpool shape, porosity, relative density, spatter, d/l·d/w·l/w and provenance columns can never enter the input or query. 5-way mode is imbalanced (~55:1). T-AM1/T-AM2 = AM task extension (metadata.taxonomy_note).

Provenance & licensing

Underlying source: MeltpoolNet — a meta-aggregation of ~hundreds of AM papers. Upstream license: no LICENSE (repo default = all-rights-reserved); meta-aggregation -> per-source clearance needed. Converted read-only into the unified schema; conversion + publish scripts live in AI4Manufacturing/forge_model (AM13_MeltpoolNet/ + publish/push_am_to_hf.py). Access is gated (manual approval); clear the upstream licence before any onward redistribution.

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