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README.md
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### Model Overview
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This model has the same configuration as the [bert-base-uncased model](https://huggingface.co/bert-base-uncased):
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12 hidden layers, 768 hidden dimensionality, 12 attention heads, ~110M parameters
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### Usage
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Using the tokenizer (same as [LegalBERT](https://huggingface.co/nlpaueb/legal-bert-base-uncased))
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Ghosh, Saptarshi",
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eprinttype = {arXiv}
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}
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```
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### Model Overview
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This model has the same configuration as the [bert-base-uncased model](https://huggingface.co/bert-base-uncased):
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12 hidden layers, 768 hidden dimensionality, 12 attention heads, ~110M parameters.
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### Usage
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Using the tokenizer (same as [LegalBERT](https://huggingface.co/nlpaueb/legal-bert-base-uncased))
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Ghosh, Saptarshi",
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eprinttype = {arXiv}
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}
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```
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### About Us
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We are a group of researchers from the Department of Computer Science and Technology, Indian Insitute of Technology, Kharagpur.
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Our research interests are primarily ML and NLP applications for the legal domain, with a special focus on the challenges and oppurtunites for the Indian legal scenario.
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We have, and are currently working on several legal tasks such as:
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* named entity recognition, summarization of legal documents
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* semantic segmentation of legal documents
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* legal statute identification from facts, court judgment prediction
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* legal document matching
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You can find our publicly available codes and datasets [here](https://github.com/Law-AI)
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