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Indic Verse
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🌏 IndicVerse
IndicVerse is dedicated to advancing natural language processing (NLP) capabilities for Indic languages. Our mission is to bridge the gap in NLP research for low-resource Indic languages by providing high-quality datasets, pre-trained models, and tools tailored for diverse linguistic needs.
🚀 What We Do
- Datasets: Creation and publication of datasets for various NLP tasks, including translation, classification, and generation, with a focus on Indic languages.
- Models: Development of state-of-the-art NLP models fine-tuned for Indic languages, leveraging techniques like PEFT and LoRA.
- Research: Conducting and sharing research to solve key challenges in Indic NLP, including transliteration, low-resource learning, and domain-specific applications.
📚 Featured Projects
- Hellaswag-Telugu: A Telugu version of the Hellaswag dataset for advanced evaluation.
- Indic Language Translation and Transliteration: Custom tools and APIs for translation and mixed transliteration (Telugu-English).
🛠️ How to Contribute
We welcome contributions! Whether you’re interested in annotating data, building models, or sharing insights, feel free to get in touch.
🌐 Links
📜 Citation
If you use our datasets or models in your research, please cite us as follows:
@misc{IndicVerse2024,
author = {Nikhil Chowdary Paleti and Divi Eswar Chowdary},
title = {Indic Verse: Datasets and Models for Advancing Indic Languages in NLP},
year = {2024},
publisher = {HF中国镜像站},
url = {https://huggingface.co/IndicVerse}
}
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indiehackers/hellaswag-telugu-custom-2k
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indiehackers/hellaswag-telugu-custom
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indiehackers/winogrande_debiased-telugu_filtered
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indiehackers/databricks-dolly-15k-Telugu-romanized
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indiehackers/winogrande_debiased-telugu-romanized-nodict
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indiehackers/winogrande_debiased-telugu-romanized
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indiehackers/winogrande_debiased-telugu
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indiehackers/telugu_romanized_2000_mistral
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indiehackers/telugu_romanized_2048_mistral
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indiehackers/telugu_romanized
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