README.md

---
tags:
- marathi
- translation
- text-classification
- semantic-search
- nlp
- ai
- deep-learning
- language-models
- text-processing
- multilingual
- huggingface-dataset
- dataset

language:
- mr

license: cc-by-nc-nd-4.0

task_categories:
- text-classification
- text-retrieval
- sentence-similarity
- token-classification
- question-answering
- zero-shot-classification
- summarization
- text-generation
- text2text-generation
- multiple-choice
- document-question-answering

size_categories:
- 100K<n<1M

pretty_name: All Nli Marathi Dataset

dataset_info:
  author: Chandan Singh
  private: true
  dataset_size: 246.89 MB (0.24 GB)
  num_rows: 570810
  num_columns: 3
  Description: "This dataset contains high-quality Marathi-translated all_nli_marathi dataset, verified by native Marathi speakers. It is designed for various NLP tasks such as semantic search, text classification, and contextual understanding."
---

# **All Nli Marathi Dataset: High-Quality Marathi NLP Corpus**

## 📌 **Overview**
The **All Nli Marathi dataset** is a meticulously curated collection of **570810** rows of Marathi text, ensuring linguistic accuracy and natural flow. Every sentence has been **verified by native Marathi speakers** to maintain **contextual integrity and correctness**.

This dataset is designed for **semantic search, text classification, and various NLP tasks**, making it a valuable resource for **machine learning models dealing with Marathi language understanding**.

---

## 🔥 **Key Features**
✅ **High-Quality Marathi Data** – Professionally curated and reviewed.  
✅ **Native Speaker Verification** – Every row is manually checked for accuracy.  
✅ **Optimized for NLP Tasks** – Useful for **semantic modeling, text classification, and retrieval-based applications**.  
✅ **Clean and Structured Data** – Ready-to-use for deep learning and transformer models.  
✅ **Supports Diverse Use Cases** – Ideal for **zero-shot classification, sentiment analysis, and language comprehension models**.  

---

## 📂 **Dataset Structure**
- **Language**: Marathi (`mr`)  
- **Rows**: 570810  
- **Columns**: anchor, positive, negative  
- **Size**: 246.89 MB (0.24 GB)  
- **Format**: Text corpus (structured sentences & paragraphs)  
- **Validation**: Human-reviewed for correctness  
- **Intended Use**: Training NLP models for **classification, retrieval, and understanding tasks**  

---

## 🚀 **Usage Guide**
To integrate this dataset into your NLP workflow, use the following code:

```python
from datasets import load_dataset

dataset = load_dataset("Singhchandann/all_nli_marathi")
```

The dataset can be directly used for **training, fine-tuning, and evaluating NLP models**.

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## 🔒 **License & Accessibility**  

### **📜 License: CC BY-NC-ND 4.0**  
This dataset is licensed under the **Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 (CC BY-NC-ND 4.0)** license.  

- **✅ Attribution Required:** You must provide proper credit when using this dataset after getting permission.  
- **⛔ No Commercial Use:** This dataset **cannot** be used for commercial purposes.  
- **⛔ No Modifications:** You **cannot** modify, adapt, or create derivative datasets from this work.  

For any special permissions or exceptions, please contact on: **[Author Email](mailto:[email protected])**  

🔗 **License Details:** [CC BY-NC-ND 4.0](https://creativecommons.org/licenses/by-nc-nd/4.0/)  

---

### **🔐 Access & Permissions**  
- This dataset is **private** and **not publicly available**.  
- Only **authorized users** with explicit permission can access and utilize this dataset.  

📩 **For access requests or further inquiries, contact the dataset author.**  

---

## 📧 **Author & Contact**
- **Author**: Chandan Singh  
- **Hugging Face Profile**: [Singhchandann](https://huggingface.co/Singhchandann)  
- **Intended Users**: Researchers, NLP practitioners, and AI developers working with **Marathi text data**.  
- **github Profile**: [Singhchandann](https://github.com/Singhchandann)  
- **Gmail**: [Send an email](mailto:[email protected])

For inquiries, please reach out via Hugging Face or Github or gmail.

---

## 📊 **Example Data Samples**
### **Example 1**
```text
anchor:
मुले बाहेर खेळत आहेत.

positive:
एक किशोरवयीन मुलगा आणि मुलगी बर्फात खेळत आहेत.

negative:
मुले दोन मुलांना व्हिडिओ गेम खेळताना पाहतात.
```

### **Example 2**
```text
anchor:
वेशभूषा घातलेल्या मुलींचा एक गट उद्यानात उभा आहे.

positive:
मुली एका उद्यानात आहेत.

negative:
मुलींचा गट त्यांच्या वर्गांमध्ये असतो.
```

### **Example 3**
```text
anchor:
एक लहान मुलगा आणि मुलगी प्रशिक्षण चाके घालून पदपथावरून त्यांच्या दुचाकी चालवतात.

positive:
एक-दोन मुले सायकल चालवत आहेत.

negative:
तीन मुले झोळीवर खेळत आहेत.
```

---