hkust-nlp/deita-6k-v0
Dataset Card for Deita 6K V0 GitHub | Paper Deita is an open-sourced project designed to facilitate Automatic Data Selection for instruction tuning in Large Language Models (LLMs). This dataset includes 6k of lightweight, high-quality alignment SFT data, mainly automatically selected from the following datasets: ShareGPT (Apache 2.0 listed, no official repo found): Use the 58 K ShareGPT dataset for selection. UltraChat (MIT): Sample 105 K UltraChat dataset for selection.… See the full description on the dataset page: https://huggingface.co/datasets/hkust-nlp/deita-6k-v0.
| Author / organization | hkust-nlp |
|---|---|
| License (as declared) | mit |
| Downloads | 178 (as reported by Hugging Face) |
| Likes | 16 |
| Created | 23 October 2023 |
| Last updated at source | 31 December 2023 |
Popularity, last 3 days
178 now (+31 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Connected in the knowledge graph
- TheBloke/deita-7B-v1.0-sft-GGUFModel · used to train
Recent changes
- 16 Oct 2026 Description: Dataset Card for Deita 6K V0 GitHub | Paper Deita is an open-sourced project designed to facilitate Automatic Data Selection for instruction tuning in Large Language Models (LLMs). This dataset includes 6k of lightweight, high-quality align → Dataset Card for Deita 6K V0 GitHub | Paper Deita is an open-sourced project designed to facilitate Automatic Data Selection for instruction tuning in Large Language Models (LLMs). This dataset includes 6k of lightweight, high-quality align
Changes detected by Silytics between refreshes of the source.
More from hkust-nlp
- hkust-nlp/SimpleRL-Zoo-DataDataset
- hkust-nlp/dart-math-hardDataset
- hkust-nlp/CodeIO-PyEdu-Reasoning-RawDataset
- hkust-nlp/dart-math-uniformDataset
- hkust-nlp/agentboardDataset
- hkust-nlp/CodeIO-PyEdu-ReasoningDataset
Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 18 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.