Datasetpublic

kushalicious/research-slm-dataset

ResearchSLM Dataset Training data for fine-tuning SmolLM2-360M on structured research skills. Files File Examples Description train_data.jsonl 14,998 Multi-skill chat-format training examples eval_data.jsonl 500 Held-out evaluation set Format Each line is a JSON object: { "messages": [ {"role": "system", "content": "..."}, {"role": "user", "content": "..."}, {"role": "assistant", "content": "{\"sub_questions\":… See the full description on the dataset page: https://huggingface.co/datasets/kushalicious/research-slm-dataset.

sourceHugging Facecc-by-sa-4.0updated 4mo agoView on Hugging Face

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Dataset Card

ResearchSLM Dataset

Training data for fine-tuning SmolLM2-360M on structured research skills.

Files

File	Examples	Description
`train_data.jsonl`	14,998	Multi-skill chat-format training examples
`eval_data.jsonl`	500	Held-out evaluation set

Format

Each line is a JSON object:

json

{
  "messages": [
    {"role": "system", "content": "..."},
    {"role": "user", "content": "..."},
    {"role": "assistant", "content": "{\"sub_questions\": [...]}"}
  ],
  "metadata": {"skill": "decomposition", "source": "hotpot_qa", "id": "hotpot_00001"}
}

Skills

decomposition, search_planning, evidence_extraction, gap_detection, contradiction_identification, follow_up_queries, synthesis

Sources

—HotPotQA — rule-based trace construction (no LLM teacher)
—Synthetic contradictions — FEVER-style conflicting claims

Build from scratch

bash

git clone https://github.com/kushalicious/research-slm.git
cd research-slm
python data/build_traces.py --max-examples 2000
python data/build_contradictions.py --max-examples 1500
python data/prepare_dataset.py --eval-size 500

Model

Trained adapter: kushalicious/research-slm-360m-lora