---
license: apache-2.0
task_categories:
- text-generation
- text-classification
- zero-shot-classification
language:
- ks
pretty_name: Poet_dataset
---
# Shruks Analysis

## Total Number of Shruks:
1552

## Total Lines 
8283

## Total Number of Words:
35992

## Total Number of Characters:
195236

### 2. **Dataset Structure for NLP Tasks**

You can use the **Shruks** dataset for various NLP tasks.


You can apply this methodology to any task, whether it's text classification, sentiment analysis, or machine translation.

### 4. **Potential Use Cases for This Dataset**

- **Text Classification:** Classifying Shruks into categories like moral lessons, nature, or philosophy.
- **Text Generation:** Training a model to generate Shruks.
- **Sentiment Analysis:** Analyzing the emotional tone of each Shruk.
- **Machine Translation:** Translating Shruks from Kashmiri to other languages.
- **Named Entity Recognition:** Extracting entities such as persons, places, and events from Shruks.
- **And more
### 5. **Tools and Libraries to Use**

- **NLTK (Natural Language Toolkit):** For tokenization, text cleaning, and pre-processing tasks.
- **spaCy:** For Named Entity Recognition, dependency parsing, and other NLP tasks.
- **TensorFlow / PyTorch:** For training machine learning models like text classification or translation models.
- **Hugging Face Transformers:** For training state-of-the-art models like BERT or GPT for various NLP tasks.