Create README.md

README.md

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+---
+language:
+- hi
+- en
+- multilingual
+license: cc-by-4.0
+tags:
+- hi
+- en
+- codemix
+datasets:
+- L3Cube-HingCorpus
+---
+
+## HingFT
+HingFT is a Hindi-English code-mixed fast text embedding model trained on Roman + Devanagari text of L3Cube-HingCorpus.
+<br>
+[dataset link] (https://github.com/l3cube-pune/code-mixed-nlp)
+
+More details on the dataset, models, and baseline results can be found in our [paper] (https://arxiv.org/abs/2204.08398)
+
+### Citing:
+```
+@inproceedings{nayak-joshi-2022-l3cube,
+    title = "{L}3{C}ube-{H}ing{C}orpus and {H}ing{BERT}: A Code Mixed {H}indi-{E}nglish Dataset and {BERT} Language Models",
+    author = "Nayak, Ravindra  and Joshi, Raviraj",
+    booktitle = "Proceedings of the WILDRE-6 Workshop within the 13th Language Resources and Evaluation Conference",
+    month = jun,
+    year = "2022",
+    address = "Marseille, France",
+    publisher = "European Language Resources Association",
+    url = "https://aclanthology.org/2022.wildre-1.2",
+    pages = "7--12",
+}
+```