Datasets:

PNLPhub
/

FarsInstruct

@@ -666,117 +666,30 @@ configs:
   - split: test
     path: xl_wic/test-*
 ---
-# Dataset Card for Dataset Name
-<!-- Provide a quick summary of the dataset. -->
-This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
-## Dataset Details
-### Dataset Description
-<!-- Provide a longer summary of what this dataset is. -->
-- **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-### Dataset Sources [optional]
-<!-- Provide the basic links for the dataset. -->
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-## Uses
-<!-- Address questions around how the dataset is intended to be used. -->
-### Direct Use
-<!-- This section describes suitable use cases for the dataset. -->
-[More Information Needed]
-### Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-[More Information Needed]
-## Dataset Structure
-<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
-[More Information Needed]
-## Dataset Creation
-### Curation Rationale
-<!-- Motivation for the creation of this dataset. -->
-[More Information Needed]
-### Source Data
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
-#### Data Collection and Processing
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-[More Information Needed]
-#### Who are the source data producers?
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-[More Information Needed]
-### Annotations [optional]
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
-#### Annotation process
-<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
-[More Information Needed]
-#### Who are the annotators?
-<!-- This section describes the people or systems who created the annotations. -->
-[More Information Needed]
-#### Personal and Sensitive Information
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
-[More Information Needed]
-## Bias, Risks, and Limitations
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-[More Information Needed]
-### Recommendations
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
-## Citation
 <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
-**BibTeX:**
 ```bibtex
 @misc{mokhtarabadi2024farsinstructempoweringlargelanguage,
       title={FarsInstruct: Empowering Large Language Models for Persian Instruction Understanding},

   - split: test
     path: xl_wic/test-*
 ---
+<p align="center">
+  <img src="https://huggingface.co/datasets/PNLPhub/FarsInstruct/resolve/main/photo_2024-09-13_11-13-49.jpg" width="200" height="200">
+</p>
+## Dataset Description
+- **Homepage:** https://github.com/Hojjat-Mokhtarabadi/FarsInstruct
+- **Repository:** https://github.com/Hojjat-Mokhtarabadi/promptsource
+- **Paper:** [FarsInstruct: Empowering Large Language Models for Persian Instruction Understanding](https://arxiv.org/abs/2407.11186)
+- **Point of Contact:** [Hojjat Mokhtarabadi](mailto:hmokhtarabadi.1999@gmail.com)
+### Dataset Summary
+Instruction-tuned large language models, such as T0, have demonstrated remarkable capabilities in following instructions across various domains. However, their proficiency remains notably deficient in many low-resource languages. To address this challenge, we introduce FarsInstruct: a comprehensive instruction dataset designed to enhance the instruction-following ability of large language models specifically for the Persian language, a significant yet underrepresented language globally. FarsInstruct encompasses a wide range of task types and datasets, each containing a mix of straightforward to complex manual written instructions, as well as translations from Public Pool of Prompts, ensuring a rich linguistic and cultural representation. As of the current writing, FarsInstruct comprises more than 200 templates across 21 distinct datasets, and we intend to update it consistently, thus augmenting its applicability.
+### Supported tasks
+<img src="https://huggingface.co/datasets/PNLPhub/FarsInstruct/resolve/main/high-quality.jpeg" width="900" height="500"> Figure 1: Detailed depiction of 11 task types utilized in our dataset. Each box within the figure lists the specific
+datasets associated with the respective task type. Datasets designated for training are highlighted in blue, and those
+reserved for testing are marked in orange. Additionally, manual datasets, which have been specifically curated and
+prompted by our team, are enclosed with solid borders. In contrast, datasets that have been translated from English
+to Persian are enclosed with dashed borders
+## Citation information
 <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
 ```bibtex
 @misc{mokhtarabadi2024farsinstructempoweringlargelanguage,
       title={FarsInstruct: Empowering Large Language Models for Persian Instruction Understanding},