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AM09_DED_energy
DED coaxial melt-pool frame -> laser-energy level P1-P4 (4-class image classification). Category B, task T-B2, in the unified Smart-Manufacturing SFT schema.
Records
62,194 records (train=62,194). Model input: a single coaxial VIS melt-pool image (590x480), bytes embedded in the image column.
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: the energy-level label — one of P1,P2,P3,P4 (text) |
reasoning |
null | no native CoT in this dataset |
cate |
"B" | SFT category |
task |
"T-B2" | unified task id |
metadata |
str (JSON) | split, provenance, units, input, license, and (for AM11/13) taxonomy_note |
Notes
Uploaded as ONE dataset (all rows together); the original train/test partition lives in metadata.split (train 43,463 / test 18,731), NOT as HF splits. The label is the source folder (P1-P4), verified by viewing pixels (P1 small/dim ... P4 large + halo).
Provenance & licensing
Underlying source: DED coaxial melt-pool imaging, Zenodo DOI 10.5281/zenodo.10421423. Upstream license: CC-BY-SA-4.0 (ShareAlike/viral) + CC-BY-4.0 (mixed on Zenodo).
Converted read-only into the unified schema; conversion + publish scripts live in
AI4Manufacturing/forge_model
(AM09_DED_energy/ + publish/push_am_to_hf.py). Access is gated (manual approval); clear the
upstream licence before any onward redistribution.
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