datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MFPT
Roles
Roles: canon repo — annot is the source label, kept machine-parseable as the gold for verification and reward parsing; there is no filled reasoning column and this repo is not itself a training view. Derived repos each state their own regime on their own card.
MFPT — bearing fault classification from the envelope spectrum (reasoning track)
Part of the AI4Manufacturing FORGE corpus (Category C, task T-C1). Each record is the envelope spectrum of a 1 s… See the full description on the dataset page: https://huggingface.co/datasets/AI4Manufacturing/MFPT.MFPT-perception
Roles
Roles: perception view of MFPT — annot is the source label (inner_race / normal / outer_race), kept machine-parseable as the gold for verification and reward parsing; the model reads query + image, where the repo ships a bearing's vibration in four image encodings as four equal-sized configs — reshaped (consecutive samples arranged as the rows of a grayscale square), scalogram (a continuous-wavelet time-scale view), spectrogram (a short-time Fourier transform) and waveform… See the full description on the dataset page: https://huggingface.co/datasets/AI4Manufacturing/MFPT-perception.MFPT-annotated
Roles
Roles: reasoning view of MFPT — annot is the source label (inner_race / normal / outer_race), kept machine-parseable as the gold for verification and reward parsing; the model reads query + image, where the image is an envelope spectrum with the theoretical fault frequencies marked. The reasoning column is filled on all 78 records and is the SFT imitation target for this repo; the query enumerates the closed set of labels the answer must come from, and annot remains the… See the full description on the dataset page: https://huggingface.co/datasets/AI4Manufacturing/MFPT-annotated.