Create README.md

README.md

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+ ---
+language: mr
+tags:
+- bert
+license: cc-by-4.0
+datasets:
+- L3Cube-MahaNews-SHC
+widget:
+- text: "IND vs IRE : आयर्लंडच्या दौऱ्यासाठी कसा आहे भारतीय संघ, जाणून घ्या कोणाला मिळाली संधी..."
+---
+
+
+## MahaNews-SHC-BERT
+
+MahaNews-SHC-BERT is a MahaBERT(<a href="https://huggingface.co/l3cube-pune/marathi-bert-v2">l3cube-pune/marathi-bert-v2</a>) model fine-tuned on full L3Cube-MahaNews-SHC Corpus, a Marathi short text / news headlines classification dataset. <br>
+It is a topic identification cum short text classification model with 12 output categories <br>
+[dataset link] (https://github.com/l3cube-pune/MarathiNLP)
+
+More details on the dataset, models, and baseline results can be found in our [paper] (coming soon)
+<br>
+Citing:
+
+```
+@article{joshi2022l3cube,
+  title={L3cube-mahanlp: Marathi natural language processing datasets, models, and library},
+  author={Joshi, Raviraj},
+  journal={arXiv preprint arXiv:2205.14728},
+  year={2022}
+}
+```
+
+Other Marathi Sentiment models from MahaNews family are shared here:<br>
+
+<a href="https://huggingface.co/l3cube-pune/marathi-topic-long-doc"> MahaNews-LDC-BERT (long documents) </a> <br>
+<a href="https://huggingface.co/l3cube-pune/marathi-topic-short-doc"> MahaNews-SHC-BERT (short text) </a> <br>
+<a href="https://huggingface.co/l3cube-pune/marathi-topic-medium-doc"> MahaNews-LPC-BERT (medium paragraphs) </a> <br>
+<a href="https://huggingface.co/l3cube-pune/marathi-topic-all-doc"> MahaNews-All-BERT (all document lengths) </a> <br>