Duplicate from AmanMussa/kazakh-instruction-v2

Co-authored-by: Mussa Aman <AmanMussa@users.noreply.huggingface.co>

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README.md

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+---
+license: mit
+task_categories:
+- question-answering
+- text-generation
+language:
+- kk
+size_categories:
+- 10K<n<100K
+---
+# Dataset Card for Dataset Name
+
+Self-instruct data pairs for Kazakh language
+
+
+## Dataset Details
+
+The dataset is translated from Standford Alpaca instruction dataset via Google Translations API.
+
+1. Manually fixed the translation error.
+2. Common names and places of Kazakhstan were added.
+3. Intructions of kazakhstan history and cultures were added.
+
+### Dataset Description
+
+
+
+
+- **Curated by:** Mussa Aman
+- **Language(s) (NLP):** Kazakh
+- **License:** MIT
+
+
+## Uses
+
+This dataset is curated to fine-tune the LLaMA 2 model for the Kazakh language. It aims to enhance the model's understanding and processing capabilities of Kazakh, addressing a gap in the Low Resource Lanuguages for solving the NLP resources for Kazakh language. 
+
+The dataset includes the self-instruct approach, there is commonly one "instruction","input" and "output" which is crucial for improving language comprehension and task performance of the model.
+
+
+## Citation
+
+**BibTeX:**
+
+@inproceedings{mussa2025parameter,
+  title={Parameter-Efficient Fine-Tuning of LLaMA 2 for the Kazakh Language: Advancing Low-Resource Language Models},
+  author={Mussa, Aman and Mansurova, Madina},
+  booktitle={International Congress on Information and Communication Technology},
+  pages={511--520},
+  year={2025},
+  organization={Springer}
+}
+**APA:**
+
+Mussa, A., & Mansurova, M. (2025, February). Parameter-Efficient Fine-Tuning of LLaMA 2 for the Kazakh Language: Advancing Low-Resource Language Models. In International Congress on Information and Communication Technology (pp. 511-520). Singapore: Springer Nature Singapore.
+
+
+
+## Dataset Card Contact
+
+Please contact in email: mussa.aman@kaznu.kz

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