Instructions to use ArthaLabs/panini-tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArthaLabs/panini-tokenizer with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ArthaLabs/panini-tokenizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files
README.md
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**The first grammar-first Sanskrit tokenizer based on Pāṇinian morphological analysis.**
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## 🚨 The Problem
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Statistical tokenizers (BPE/WordPiece) systematically underperform on Sanskrit because they do not model **Sandhi**(phonetic fusion).
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**The first grammar-first Sanskrit tokenizer based on Pāṇinian morphological analysis.**
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[](https://huggingface.co/spaces/ArthaLabs/panini-tokenizer-demo)
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## 🚨 The Problem
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Statistical tokenizers (BPE/WordPiece) systematically underperform on Sanskrit because they do not model **Sandhi**(phonetic fusion).
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