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---
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tags:
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- marathi
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- translation
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- text-classification
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- semantic-search
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- nlp
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- ai
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- deep-learning
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- language-models
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- text-processing
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- multilingual
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- huggingface-dataset
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- dataset
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language:
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- mr
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license: cc-by-nc-nd-4.0
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task_categories:
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- text-classification
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- text-retrieval
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- sentence-similarity
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- token-classification
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- question-answering
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- zero-shot-classification
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- summarization
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- text-generation
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- text2text-generation
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- multiple-choice
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- document-question-answering
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size_categories:
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- 100K<n<1M
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pretty_name: Nli-For-Simcse Marathi Dataset
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dataset_info:
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author: Chandan Singh
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private: true
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dataset_size: 124.87 MB (0.12 GB)
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num_rows: 274951
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num_columns: 3
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Description: "This dataset contains high-quality Marathi-translated nli-for-simcse_marathi dataset, verified by native Marathi speakers. It is designed for various NLP tasks such as semantic search, text classification, and contextual understanding."
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---
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# **Nli-For-Simcse Marathi Dataset: High-Quality Marathi NLP Corpus**
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## 📌 **Overview**
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The **Nli-For-Simcse Marathi dataset** is a meticulously curated collection of **274951** 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**.
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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**.
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---
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## 🔥 **Key Features**
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✅ **High-Quality Marathi Data** – Professionally curated and reviewed.
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✅ **Native Speaker Verification** – Every row is manually checked for accuracy.
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✅ **Optimized for NLP Tasks** – Useful for **semantic modeling, text classification, and retrieval-based applications**.
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✅ **Clean and Structured Data** – Ready-to-use for deep learning and transformer models.
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✅ **Supports Diverse Use Cases** – Ideal for **zero-shot classification, sentiment analysis, and language comprehension models**.
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---
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## 📂 **Dataset Structure**
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- **Language**: Marathi (`mr`)
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- **Rows**: 274951
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- **Columns**: anchor, positive, negative
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- **Size**: 124.87 MB (0.12 GB)
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- **Format**: Text corpus (structured sentences & paragraphs)
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- **Validation**: Human-reviewed for correctness
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- **Intended Use**: Training NLP models for **classification, retrieval, and understanding tasks**
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---
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## 🚀 **Usage Guide**
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To integrate this dataset into your NLP workflow, use the following code:
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```python
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from datasets import load_dataset
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dataset = load_dataset("Singhchandann/nli-for-simcse_marathi")
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```
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The dataset can be directly used for **training, fine-tuning, and evaluating NLP models**.
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---
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Here’s a properly structured and refined version of your license section:
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---
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## 🔒 **License & Accessibility**
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### **📜 License: CC BY-NC-ND 4.0**
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This dataset is licensed under the **Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 (CC BY-NC-ND 4.0)** license.
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- **✅ Attribution Required:** You must provide proper credit when using this dataset after getting permission.
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- **⛔ No Commercial Use:** This dataset **cannot** be used for commercial purposes.
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- **⛔ No Modifications:** You **cannot** modify, adapt, or create derivative datasets from this work.
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For any special permissions or exceptions, please contact on: **[Author Email](mailto:[email protected])**
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🔗 **License Details:** [CC BY-NC-ND 4.0](https://creativecommons.org/licenses/by-nc-nd/4.0/)
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---
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### **🔐 Access & Permissions**
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- This dataset is **private** and **not publicly available**.
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- Only **authorized users** with explicit permission can access and utilize this dataset.
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📩 **For access requests or further inquiries, contact the dataset author.**
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---
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## 📧 **Author & Contact**
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- **Author**: Chandan Singh
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- **Hugging Face Profile**: [Singhchandann](https://huggingface.co/Singhchandann)
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- **Intended Users**: Researchers, NLP practitioners, and AI developers working with **Marathi text data**.
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- **github Profile**: [Singhchandann](https://github.com/Singhchandann)
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- **Gmail**: [Send an email](mailto:[email protected])
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For inquiries, please reach out via Hugging Face or Github or gmail.
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---
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## 📊 **Example Data Samples**
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### **Example 1**
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```text
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anchor:
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हिरव्या रंगाचा टी-शर्ट घातलेला एक माणूस त्याच्या कार्यालयात काम करतो.
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positive:
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एक माणूस घरामध्ये काम करत आहे.
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negative:
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तो माणूस मेलबॉक्सकडे जात आहे.
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```
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### **Example 2**
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```text
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anchor:
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लोकांचा एक गट मरीनासमोर हवाई रॉकेट प्रक्षेपित करतो.
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positive:
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ते घराबाहेर आहेत.
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negative:
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ते वाळवंटात आहेत.
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```
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### **Example 3**
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```text
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anchor:
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त्यांचा वेग कमी करण्यासाठी आपण ते वाढवू शकतो परंतु ते त्यांना फार काळ थांबवू शकणार नाही.
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positive:
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ती वाढवून आपण त्यांचा वेग कमी करू शकतो.
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negative:
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त्यांचा वेग कमी करण्याचा कोणताही मार्ग नाही.
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```
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---
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