Added AI-powered synthetic dataset generator demo

community-contributions/synthetic-dataset-generator/README.md

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+# LLM-Powered Dataset Synthesizer: LLaMA 3 + Gradio Demo
+
+This interactive demo showcases a synthetic dataset generation pipeline powered by Meta's LLaMA 3.1 8B-Instruct model, running in 4-bit quantized mode. Users can input natural language prompts describing the structure and logic of a desired dataset, and the model will generate tabular data accordingly.
+
+## ✨ Description
+
+Modern LLMs are capable of reasoning over structured data formats and generating realistic, constrained datasets. This demo leverages the LLaMA 3.1 instruct model, combined with prompt engineering, to generate high-quality synthetic tabular data from plain-language descriptions.
+
+Key components:
+- **LLaMA 3.1 8B-Instruct** via Hugging Face Transformers
+- **4-bit quantized loading** with `bitsandbytes` for memory efficiency
+- **Custom prompt framework** for schema + value constraints
+- **Interactive interface** built with Gradio for user-friendly data generation
+
+## 🚀 Functionality
+
+With this tool, you can:
+- Generate synthetic datasets by describing the column names, data types, value logic, and number of rows
+- Apply constraints based on age, gender, matching conditions, and more (e.g., “females over 40; males under 40”)
+- Preview the raw model output or extract structured JSON/tabular results
+- Interactively explore and copy generated datasets from the Gradio UI
+
+## 🛠️ Under the Hood
+
+- The model prompt template includes both a **system message** and user instruction
+- Output is parsed to extract valid JSON objects
+- The generated data is displayed in the Gradio interface and downloadable as CSV
+
+## 📦 Requirements
+
+- Python (Colab recommended)
+- `transformers`, `bitsandbytes`, `accelerate`, `gradio`, `torch`
+- Hugging Face access token with permission to load LLaMA 3.1
+
+---
+
+Ready to generate smart synthetic datasets with just a sentence? Try it!