metadata

license: mit
task_categories:
  - text-classification
  - token-classification
  - table-question-answering
  - question-answering
  - zero-shot-classification
  - translation
  - summarization
  - feature-extraction
  - text-generation
  - text2text-generation
  - sentence-similarity
  - fill-mask
  - text-to-speech
  - text-to-audio
  - automatic-speech-recognition
  - audio-to-audio
  - audio-classification
  - voice-activity-detection
  - depth-estimation
  - image-classification
  - object-detection
  - image-segmentation
  - text-to-image
  - image-to-text
  - image-to-image
  - image-to-video
  - unconditional-image-generation
  - video-classification
  - reinforcement-learning
  - tabular-classification
  - robotics
  - tabular-regression
  - tabular-to-text
  - table-to-text
  - multiple-choice
  - text-retrieval
  - time-series-forecasting
  - text-to-video
  - visual-question-answering
  - zero-shot-image-classification
  - graph-ml
  - mask-generation
  - zero-shot-object-detection
  - image-to-3d
  - text-to-3d
  - image-feature-extraction
  - video-text-to-text
language:
  - en
  - es
  - af
tags:
  - chemistry
  - biology
  - finance
  - legal
  - music
  - art
  - code
  - synthetic
  - climate
size_categories:
  - n>1T
pretty_name: update_8

Rich & engaging dataset card:

Uses:

🗨️text-to-image🧏‍♂️
🚗auto-tuning dataset📈
🏘️hosted on Hugging Face🤗

This is a comprehensive and detailed version that covers all the necessary fields.

This version🆚 also includes lots of emojis

Emojis are designed enhance readability and engagement!

📚💍🙏🆘💁‍♀️💡🔦🩵🚦〽️🏋️‍♀️🔥
🛟👄🎧🦁👅♌👂⚖️🪪🫠😋🛋️
🧧🍋🦵🐸🦎

~

license: mit
task_categories:
- text-to-image
- unconditional-image-generation
language:
- en
- es
tags:
- finance
- biology
- chemistry
- code
- art
- synthetic
pretty_name: My Auto-Tune Dataset 🖼️🎨
size_categories:
- n>1T
---

📄 Dataset Card for My Auto-Tune Dataset

📚 Dataset Summary

🚀 This dataset is designed to fine-tune models for generating high-quality images from text prompts. Whether you're into art, synthetic data, or creative AI, this dataset is your go-to source for automatic image generation! 🌐🖌️

🧩 Dataset Details

🔍 Description

🔧 This dataset includes a massive collection of text-image pairs to train and fine-tune text-to-image models. With multi-lingual support (English & Spanish) 🌍, it's perfect for applications in fields such as finance, biology, chemistry, and even code-based art generation! 💸🧬⚛️👾

🔄 Dataset Sources

Repository: nivin-ai/faq_embeddings
Paper [optional]: Currently, there is no associated paper 📄.
Demo [optional]: Coming soon! 🚧

💡 Intended Uses

✅ Direct Use

Fine-tuning models for text-to-image generation 🎨.
Building creative AI systems for generating unique visuals 🖼️.
Developing models in art, synthetic data, and finance contexts 💰.

🚫 Out-of-Scope Use

⚠️ Do not use this dataset for generating harmful, explicit, or misleading content.
Avoid applications in real-time decision-making systems where accuracy is critical 🛑.

🏗️ Dataset Structure

File Types: .jsonl for text-image pairs 🗂️.
Splits: Train and validation splits are defined as follows:
- train/: 80% of the data 🏋️‍♂️
- validation/: 20% for model evaluation 🧪
- train/: 20% of the data 🏋️‍♂️
- validation/: 5% for model evaluation 🧪
- train/: 100% of the data 🏋️‍♂️
- validation/: 25% for model evaluation 🧪

⚙️ Dataset Creation Process

🎯 Curation Rationale

The dataset was developed to empower researchers and developers to create state-of-the-art text-to-image generation models. It's optimized for large-scale projects requiring high-quality visual outputs 🚀.

🏗️ Source Data

Collection Process: Scraped from open-source text and image databases 📂.
Processing: All text entries were normalized, and images were resized for consistent input dimensions 🖼️.

✏️ Annotations

Annotation Process: Annotations include descriptions and metadata for images 🌟.
Annotators: Curated by experts in AI, finance, and art domains 🎓.
Tools Used: Hugging Face’s datasets library and custom Python scripts 🐍.

🔍 Bias, Risks, and Limitations

While this dataset aims to provide neutral and creative content, users should be aware that:

It may contain biases inherent in its source data 🧐.
The dataset should not be used for generating inappropriate or offensive content 🚫.
May not be suitable for mission-critical applications (e.g., medical, legal, or financial advice) ⚠️.

🌟 Recommendations

Always evaluate model outputs for biases and inaccuracies before deployment.
Use responsibly, especially if integrating with sensitive applications 💼.

🔗 Citations

If you use this dataset, please cite:

@misc{my_auto_tune_dataset_2024,
  title={My Auto-Tune Dataset},
  author={Derrick Adkison, Kumplex Media Holdings Group LLC},
  year={2024},
  url={https://huggingface.co/nivin-ai/faq_embeddings},
  license={MIT}
}


---

📞 Contact Information

Author: Derrick Adkison

Organization: Kumplex Media Holdings Group LLC

Email: [email protected]

Alternate Email: [email protected]

Phone: +1 253-293-2802 ☎️



---

📖 Glossary


---

🔍 More Information

For any questions, open an issue on the GitHub repository or contact us directly 📧.


---

🤖 Dataset Card Authors

Derrick Adkison

Contributors: Hugging Face Community 🧑‍🤝‍🧑



---

This dataset card covers all essential fields and includes fun, emoji-filled explanations to make it engaging for users. Let me know if you need more tweaks or additional fields!


~~~