aplycaebous/BanTH
BanTH: A Multi-label Hate Speech Detection Dataset for Transliterated Bangla Dataset Overview Hate detection (binary) and target identification (multi-label) dataset on 37.3 k transliterated Bangla samples. ~38% hate samples and 7 target classes: Political, Religious, Gender, Personal Offense, Abusive/Violence, Origin, and Body Shaming. Sourced from 26 YouTube channels of 3 categories: News & Politics, People & Blogs, and Entertainment. Each sample is labeled by… See the full description on the dataset page: https://huggingface.co/datasets/aplycaebous/BanTH.
| Author / organization | aplycaebous |
|---|---|
| License (as declared) | mit |
| Downloads | 274 (as reported by Hugging Face) |
| Likes | 1 |
| Created | 25 March 2025 |
| Last updated at source | 25 March 2025 |
Popularity, last 5 days
274 now (+20 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Connected in the knowledge graph
- algolyzer/laya-banglaModel · used to train
- algolyzer/laya-bangla-loraModel · used to train
Recent changes
- 16 Oct 2026 Description: BanTH: A Multi-label Hate Speech Detection Dataset for Transliterated Bangla Dataset Overview Hate detection (binary) and target identification (multi-label) dataset on 37.3 k transliterated Bangla samples. ~38% hate samples and 7 target cl → BanTH: A Multi-label Hate Speech Detection Dataset for Transliterated Bangla Dataset Overview Hate detection (binary) and target identification (multi-label) dataset on 37.3 k transliterated Bangla samples. ~38% hate samples and 7 target cl
Changes detected by Silytics between refreshes of the source.
More from aplycaebous
- aplycaebous/BnSentMixDataset
Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 20 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.