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1. NepTam-A-Nepali-Tamang-Parallel-Corpus-and-Baseline-Machine-Translation-Experiments NepTam-A-Nepali-Tamang-Parallel-Corpus-and-Baseline-Machine-Translation-Experiments Public

   Parallel corpus for Nepali-Tamang machine translation and Baseline experiments

   Jupyter Notebook 1

2. LLMs-for-NER-and-POS-Tagging-in-Nepali-context LLMs-for-NER-and-POS-Tagging-in-Nepali-context Public

   This work attempts to investigate the potential of different LLMs especially BERT variants for Named-Entity Recognition (NER) and Part-of-Speech (POS) Tagging task in Nepali Language.

   Jupyter Notebook 2

3. CNN-Transformer-based-Encoder-Decoder-Model-for-Nepali-Image-Captioning CNN-Transformer-based-Encoder-Decoder-Model-for-Nepali-Image-Captioning Public

   Image Captioning using CNN (for image features extraction) and Transformer (for language modelling) in Nepali Language.

   Jupyter Notebook 1

4. Flickr8k_Nepali_Dataset Flickr8k_Nepali_Dataset Public

   The dataset contains flickr8k image captions in Nepali. The English captions are translated using Google translate API. It contains more than 40,000 Nepali image-caption pairs. The images can be do…

5. Benchmarking-BERT-based-Models-for-Sentence-level-Topic-Classification-in-Nepali-Language Benchmarking-BERT-based-Models-for-Sentence-level-Topic-Classification-in-Nepali-Language Public

   This project benchmarks BERT-based models for sentence-level topic classification in Nepali, a low-resource language. Using 25K labeled sentences across five domains, it shows Indic models, especia…

   Jupyter Notebook 1

6. Nepali-Video-Captioning-using-CNN-RNN-Architecture Nepali-Video-Captioning-using-CNN-RNN-Architecture Public

   Video Captioning using CNN (for image features extraction) and RNN (for language modelling) in Nepali Language.

   Jupyter Notebook