Welcome to the GitHub repository containing a diverse conversational dataset with over 100,000 to 1,000,000 entries. This dataset is perfect for Natural Language Processing (NLP) projects, chatbots, and other applications requiring realistic and engaging conversational interactions.
jokes.csv: A CSV file containing thousands of jokes.questions_responses.csv: A CSV file with thousands of question-answer pairs.README.md: This file describing the repository and how to use the dataset.
- Format : CSV files with various columns depending on the data type.
- Total Entries : Over 100,000 to 1,000,000
- Types of Data :
- Jokes: Puns, Q&A jokes, humorous observations, etc.
- Question-Answer Pairs: Diverse topics including general knowledge, personal experiences, opinions, etc.
- Other conversational entries as appropriate.
- "Where do superheroes shop? At the supermarket. 🦸♂️🛒"
- "Why do scuba divers always fall backwards? Because if they fell forwards, they'd still be in the boat! 😆"
- "What do you call a dog that does magic tricks? A labracadabrador! 🐶✨"
| Question | Answer |
|---|---|
| "What's your favorite food?" | "Oh, I love pizza 🍕! What about you?" |
| "Have you ever traveled abroad?" | "Yes, I went to Japan last year. It was amazing! 🇯🇵✨" |
| "What do you think about modern technology?" | "I find it fascinating 🤖. The advancements are impressive!" |
| "Tell me a joke." | "Why do scuba divers always fall backwards? Because if they fell forwards, they'd still be in the boat! 😆" |
You can use this dataset for:
- Training Natural Language Processing (NLP) models.
- Enhancing chatbots with realistic conversational interactions.
- Analyzing conversational patterns and common expressions.
- Any other project involving human-AI interactions.
Clone the repository to get the dataset:
git clone https://github.com/JeremGamingYT/TrainAIDatasets.gitContributions are welcome! If you have additional data entries or suggestions to improve the dataset, feel free to open an issue or submit a pull request.
- Fork this repository
- Create your feature branch (
git checkout -b feature/AmazingFeature) - Commit your changes (
git commit -m 'Add some AmazingFeature') - Push to the branch (
git push origin feature/AmazingFeature) - Open a Pull Request
This project is licensed under the MIT License. See the LICENSE file for details.
Thank you to everyone who contributes to making this dataset better! I hope you find this dataset useful and interesting. Enjoy!
Feel free to adjust any part of this README to better fit your specific project and preferences.