Datasets:

AI4Manufacturing
/

EMB-D29

dataset_info:
  features:
    - name: query
      dtype: string
    - name: image
      dtype: 'null'
    - name: annot
      list: string
    - name: reasoning
      dtype: 'null'
    - name: cate
      dtype: string
    - name: task
      dtype: string
    - name: metadata
      dtype: string
  splits:
    - name: train
      num_bytes: 391474
      num_examples: 680
    - name: val
      num_bytes: 134494
      num_examples: 234
    - name: test
      num_bytes: 128615
      num_examples: 224
  download_size: 239714
  dataset_size: 654583
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: val
        path: data/val-*
      - split: test
        path: data/test-*
extra_gated_prompt: >-
  This dataset is released for **research use**. Access is reviewed and granted
  **manually** by the maintainers. Please state your name, affiliation, and
  intended use.
tags:
  - smart-manufacturing
  - sft
  - industrial
license: other
pretty_name: EMB-D29
extra_gated_fields:
  Name: text
  Affiliation: text
  Intended use: text

EMB-D29

ISO-knowledge retrieval tasks (query → relevant set) in the unified SFT schema. Category A (knowledge), task T-A2.

The repository name is an internal code. See Provenance below for the underlying dataset.

Records

1,138 records with real train / val / test splits (680 / 234 / 224); each record's metadata.split matches its split. Deterministic, LLM-free rebuild of the official task-construction pipeline (fixed seed = 42).

Unified SFT schema (7 fields)

field	type	meaning
`query`	str	the question / query / instruction
`image`	Image \| null	always `null` in this dataset
`annot`	str \| list[str]	label / answer / annotation
`reasoning`	str \| null	native reasoning / CoT; null when the source has none
`cate`	"A".."E"	one of the five SFT categories (this dataset: A)
`task`	"T-xx"	unified task id (this dataset: T-A2)
`metadata`	str (JSON)	all other info; carries a "split" key when the source has train/val/test

Load

from datasets import load_dataset
ds = load_dataset("AI4Manufacturing/EMB-D29")["train"]

Gated — request access on the dataset page; access is granted manually by the maintainers.

Provenance & license

This dataset is a reformatted derivative (unified SFT schema) of:

Embedding Models monorepo (IBM Research; shares the FailureSensorIQ repository).

Code: https://github.com/IBM/FailureSensorIQ (LLM-Embeddings/)

Refer to the upstream source for the original licensing terms; this reformatted version is shared for research use. Please cite the upstream work.