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LLM Text Generation Dataset

LLM Text Generation Dataset provides high-quality training data for language models, containing diverse text generations across multiple domains to enhance generative AI capabilities

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  • logs
    4 Millions+
  • Languages
    32
  • Models of GPT
    3
  • NLP
  • LLM
  • Classification
  • Data Collection
  • GPT
  • logs
    4 Millions+
  • Languages
    32
  • Models of GPT
    3

Dataset Info

Characteristic Data
Description Generated texts to achieve higher performance in various NLP tasks
Data types Text
Tasks Generating text, answering questions and classification text
Total number of files 4,000,000+
Languages Ukrainian, Turkish, Thai, Swedish, Slovak, Portuguese (Brazil), Portuguese, Polish, Persian, Dutch, Maratham, Malayalam, Korean, Japanese, Italian, Indonesian, Hungarian, Hindi, Irish, Greek, German, French, Finnish, Esperanto, English, Danish, Czech, Chinese, Catalan, Azerbaijani, Arabic
Labeling Metadata (language, model, time of the generation, prompt, response)
Download sample

Technical
Characteristics

Characteristic Data
Models GPT GPT-3.5, GPT-4, Uncensored GPT Version
File Extension csv
Source and collection methodology: Data was collected using text generation by different GPT models.

Languages in the dataset

  • arabic
    Arabic
  • Azerbaijani
  • Catalan
  • Chinese
  • Czech
  • German
  • Greek
  • English
  • Esperanto
  • Spanish
  • Persian
  • Finnish
  • French
  • Irish
  • Hindi
  • Hungarian
  • Indonesian
  • Italian
  • Japanese
  • Korean
  • Malayalam
  • Marathi
  • Netherlands
  • Polish
  • Portuguese
  • Portuguese (Brazil)
  • Slovak
  • Swedish
  • Thai
  • Turkish
  • Ukrainian
  • arabic
    Arabic
  • Azerbaijani
  • Catalan
  • Chinese
  • Czech
  • German
  • Greek
  • English
  • Esperanto
  • Spanish
  • Persian
  • Finnish
  • French
  • Irish
  • Hindi
  • Hungarian
  • Indonesian
  • Italian
  • Japanese
  • Korean
  • Malayalam
  • Marathi
  • Netherlands
  • Polish
  • Portuguese
  • Portuguese (Brazil)
  • Slovak
  • Swedish
  • Thai
  • Turkish
  • Ukrainian

Dataset Use Cases

  • AI Research & Development

    Training and Fine-Tuning Large Language Models

    LLM Text Generation Dataset provides high-quality training data for building and improving language models. Researchers and developers use it for supervised fine-tuning, generation tasks, and evaluation of generative AI systems, including GPT models and LLaMA models. With a large corpus of synthetic texts and human-annotated examples, it enables the creation of models with advanced generation capabilities.



  • Content Creation & Automation

    Enhancing Generative AI for Writing and Media Production

    Media companies and marketing teams can use this generated text dataset to train AI for content creation, semantic search, and personalized copywriting. The dataset supports generating high-quality and contextually relevant texts for blogs, news articles, product descriptions, and social media campaigns.



  • AI Detection & Moderation

    Detecting and Classifying AI-Generated Content

    The AI-Generated Text Dataset is valuable for organizations building systems to identify and moderate synthetic data. Including both human-written and AI-generated samples, it enables text classification models to detect LLM outputs with higher precision.



  • Education & Knowledge Platforms

    Developing Intelligent Tutoring and Knowledge Retrieval Systems

    Educational technology companies use this LLM text-generated dataset to power natural language tutoring systems, semantic search, and question-answering tools. The dataset’s diversity ensures robust performance across different domains and language processing tasks.



What is included in the LLM Text Generation Dataset?
The dataset contains over 4 million generated texts across more than 30 languages, including English, Chinese, German, French, Arabic, and more. Each entry is enriched with metadata such as language, model type (GPT-3.5, GPT-4, uncensored GPT), prompt, response, and generation time, ensuring comprehensive training data for generative models.
How was the data for this dataset collected?
The data was collected from pre-trained LLM outputs such as GPT-3.5 and GPT-4. The generation process included collecting synthetic data, prompts, and responses, followed by the addition of metadata annotations to provide context for deep learning, machine learning, and supervised fine-tuning tasks.
Can I request a sample of the dataset before purchasing?
Yes. Unidata provides dataset samples so you can evaluate the text corpus quality, metadata annotations, and output formats before making a purchase. This ensures the dataset meets your requirements for training corpus preparation, generative AI research, and LLM evaluations.
Is it possible to request a custom-generated text dataset?
Yes. Unidata supports custom dataset creation, allowing you to specify languages, domain-specific prompts, and metadata requirements. This is ideal if your project demands specialized training corpus data for domain-specific LLM applications.
Still have questions about using Unidata datasets? Read our user-guides

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