QUEST-SFT-Data-Open-ended: Supervised Fine-Tuning Trajectories for Tool-Using Assistants

Open-ended supervised fine-tuning trajectories for QUEST, a tool-using assistant format. The dataset is hosted on Hugging Face by osunlp and was last updated on 2026-05-27. It contains a 'train' split with a 'messages' column structured as a list of role-content dictionaries.

Use Cases

• Fine-tuning language models for tool-use based on the described conversational trajectories.
• Training models for open-ended dialogue assistance based on the structured message format.
• Benchmarking or evaluating tool-using assistant performance based on the supervised fine-tuning data.

Strengths

• Data is structured for a specific training purpose (supervised fine-tuning) for tool-using assistants.
• Associated with the QUEST family of models, suggesting a research-backed origin.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

osunlp

Collection Method

Likely generated as part of the QUEST model training pipeline.

Freshness

Last updated 2026-05-27 04:32:24; freshness should be verified.