DeSTA-ntu/DeSTA-AQA5M-FROM-Llama3.1-8B-Instruct
๐ Paper | ๐ฉโ๐ป Github | ๐ค Model | ๐ค Dataset DeSTA-AQA5M comprises 50 speech, environmental sound, and music datasets, totaling over 7,000 hours of audio. Our training framework centers on self-generated response for efficient cross-modal alignment. (see our paper!). In DeSTA, each audio clip is first transformed into a textual description using its metadata. A Large Language Model (LLM) is then prompted with this description to self-generate a response. Ultimately, we construct aโฆ See the full description on the dataset page: https://huggingface.co/datasets/DeSTA-ntu/DeSTA-AQA5M-FROM-Llama
| Author / organization | DeSTA-ntu |
|---|---|
| Downloads | 660 (as reported by Hugging Face) |
| Likes | 5 |
| Created | 21 July 2025 |
| Last updated at source | 7 August 2025 |
Popularity, last 4 days
660 now (-29 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Connected in the knowledge graph
- DeSTA-ntu/DeSTA2.5-Audio-Llama-3.1-8BModel ยท used to train
Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 19 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.