Hindi-Doc-Topic-BERT model is an IndicSBERT(
l3cube-pune/hindi-sentence-bert-nli
) model fine-tuned on Hindi documents from the L3Cube-IndicNews Corpus [dataset link]
https://github.com/l3cube-pune/indic-nlp
.
This dataset consists of sub-datasets like LDC (Long Document Classification), LPC (Long Paragraph Classification), and SHC (Short Headlines Classification), each having different document lengths.
This model is trained on a combination of all three variants and works well across different document sizes.
@article{mirashi2024l3cube,
title={L3Cube-IndicNews: News-based Short Text and Long Document Classification Datasets in Indic Languages},
author={Mirashi, Aishwarya and Sonavane, Srushti and Lingayat, Purva and Padhiyar, Tejas and Joshi, Raviraj},
journal={arXiv preprint arXiv:2401.02254},
year={2024}
}
hindi-topic-all-doc huggingface.co is an AI model on huggingface.co that provides hindi-topic-all-doc's model effect (), which can be used instantly with this l3cube-pune hindi-topic-all-doc model. huggingface.co supports a free trial of the hindi-topic-all-doc model, and also provides paid use of the hindi-topic-all-doc. Support call hindi-topic-all-doc model through api, including Node.js, Python, http.
hindi-topic-all-doc huggingface.co is an online trial and call api platform, which integrates hindi-topic-all-doc's modeling effects, including api services, and provides a free online trial of hindi-topic-all-doc, you can try hindi-topic-all-doc online for free by clicking the link below.
l3cube-pune hindi-topic-all-doc online free url in huggingface.co:
hindi-topic-all-doc is an open source model from GitHub that offers a free installation service, and any user can find hindi-topic-all-doc on GitHub to install. At the same time, huggingface.co provides the effect of hindi-topic-all-doc install, users can directly use hindi-topic-all-doc installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
hindi-topic-all-doc install url in huggingface.co: