Update README.md

README.md

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----
-license: apache-2.0
----
+---
+language: en
+license: apache-2.0
+---
+
+# CodeRosetta
+## Pushing the Boundaries of Unsupervised Code Translation for Parallel Programmingb ([📃Paper](https://arxiv.org/abs/2410.20527), [🔗Website](https://coderosetta.com/)).
+
+
+CodeRosetta is an EncoderDecoder translation model. It supports the translation of C++, CUDA, and Fortran. \
+This version of the model is fine-tuned for **Fortran to C++ translation.**
+
+### How to use
+
+```python
+from transformers import AutoTokenizer, EncoderDecoderModel
+
+# Load the CodeRosetta model and tokenizer
+model = EncoderDecoderModel.from_pretrained('CodeRosetta/CodeRosetta_fortran2cpp_ft')
+tokenizer = AutoTokenizer.from_pretrained('CodeRosetta/CodeRosetta_fortran2cpp_ft')
+
+# Encode the input Fortran Code
+input_fortran_code = "program DRB047_doallchar_orig_no\n use omp_lib\n implicit none\n\n character(len=100), dimension(:), allocatable :: a\n character(50) :: str\n integer :: i\n\n allocate (a(100))\n\n !$omp parallel do private(str)\n do i = 1, 100\n write( str, '(i10)' ) i\n a(i) = str\n end do\n !$omp end parallel do\n\n print*,'a(i)',a(23)\nend program"
+input_ids = tokenizer.encode(input_fortran_code, return_tensors="pt")
+
+# Set the start token to <CPP>
+start_token = "<CPP>"
+decoder_start_token_id = tokenizer.convert_tokens_to_ids(start_token)
+
+# Generate the C++ code
+output = model.generate(
+    input_ids=input_ids, 
+    decoder_start_token_id=decoder_start_token_id,
+    max_length=256
+)
+
+# Decode and print the generated output
+generated_code= tokenizer.decode(output[0], skip_special_tokens=True)
+print(generated_code)
+```
+
+### BibTeX 
+
+```bibtex
+@inproceedings{coderosetta:neurips:2024,
+  title = {CodeRosetta: Pushing the Boundaries of Unsupervised Code Translation for Parallel Programming},
+  author = {TehraniJamsaz, Ali and Bhattacharjee, Arijit and Chen, Le and Ahmed, Nesreen K and Yazdanbakhsh, Amir and Jannesari, Ali},
+  booktitle = {NeurIPS},
+  year = {2024},
+}