Update README.md

README.md

@@ -1,53 +1,24 @@
-# nl2bash-custom
-
-nl2bash-custom is a custom dataset used to fine-tune Large Language Models for Bash Code Generation. Fine tune the Code-Llamma family of LLMs (7b, 13b, 70b) for best results.
-
-The dataset is created by reformatting and reshiffling of 2 original datasets
-- [nl2bash by TelinaTool](https://github.com/TellinaTool/nl2bash)
-- [NLC2CMD by Magnum Reasearch Group](https://github.com/magnumresearchgroup/Magnum-NLC2CMD)
-
-## Dataset Structure
-
-- `train.json`: Training split.
-- `dev.json`: Development split.
-- `test.json`: Test split.
-
-## Usage
-
-```python
-from datasets import load_dataset
-
-dataset = load_dataset("AnishJoshi/nl2bash-custom")
-```
-
-## Features
-
-- 'srno': Serial number of the input-output pair
-- 'nl_command': The natural language input/command
-- 'bash_code': Corresponding bash code
-
-## References
-
-@inproceedings{LinWZE2018:NL2Bash, 
-  author = {Xi Victoria Lin and Chenglong Wang and Luke Zettlemoyer and Michael D. Ernst}, 
-  title = {NL2Bash: A Corpus and Semantic Parser for Natural Language Interface to the Linux Operating System}, 
-  booktitle = {Proceedings of the Eleventh International Conference on Language Resources
-               and Evaluation {LREC} 2018, Miyazaki (Japan), 7-12 May, 2018.},
-  year = {2018} 
-}
-
-@article{Fu2021ATransform,
-  title={A Transformer-based Approach for Translating Natural Language to Bash Commands},
-  author={Quchen Fu and Zhongwei Teng and Jules White and Douglas C. Schmidt},
-  journal={2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA)},
-  year={2021},
-  pages={1241-1244}
-}
-
-@article{fu2023nl2cmd,
-  title={NL2CMD: An Updated Workflow for Natural Language to Bash Commands Translation},
-  author={Fu, Quchen and Teng, Zhongwei and Georgaklis, Marco and White, Jules and Schmidt, Douglas C},
-  journal={Journal of Machine Learning Theory, Applications and Practice},
-  pages={45--82},
-  year={2023}
-}
+# nl2linux
+
+This a custom dataset used to fine-tune Large Language Models for Linux Command Generation. 
+
+The dataset is created by filtering AnishJoshi/nl2bash-custom dataset from huggingface.
+
+## Dataset Structure
+
+- `train.json`: Training split.
+- `dev.json`: Development split.
+- `test.json`: Test split.
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("prabhanshubhowal/natural_language_to_linux")
+```
+
+## Features
+
+- 'nl_command': The natural language input/command
+- 'bash_code': Corresponding bash code