synthetic-data

A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.

medigan - A Python Library of Pretrained Generative Models for Medical Image Synthesis

Official code for NeurIPS 2024 paper LRM-Zero: Training Large Reconstruction Models with Synthesized Data

Main folder. Material related to my books on synthetic data and generative AI. Also contains documents blending components from several folders, or covering topics spanning across multiple folders..

Build an Autonomous Web3 AI Trading Agent (BASE + Uniswap V4 example)

Synthetic test data that hits the numbers you declare, exactly. Multi-table with verified foreign-key integrity, deterministic, no model in the data path. Python + MCP server.

A data-centric AI package for ML/AI. Get the best high-quality data for the best results. Discord: https://discord.gg/t6ADqBKrdZ

SynthGenAI - Package for Generating Synthetic Datasets using LLMs.

Better AI Predictions ⚡

[CVPR 2024 Highlight] ImageNet-D

A tiny language model that talks like a house cat named Miso.

Synthetic medical VQA pipeline: 119K images annotated by frontier VLMs, cross-validated at 93% agreement, fine-tuned on 3 model families (2-3B params)

[TACL, EMNLP 2025 Oral] Code, datasets, and checkpoints for the paper "CRAFT Your Dataset: Task-Specific Synthetic Dataset Generation Through Corpus Retrieval and Augmentation"

Enterprise-grade Knowledge Distillation framework for Persian Mental Health analysis. Distills reasoning capabilities from Llama-3-70b into a local Gemma-3-1b model using QLoRA and synthetic Chain-of-Thought datasets.

Synthetic data generation to fuel AI models

MediBeng Whisper Tiny improves doctor-patient transcription by training the Whisper Tiny model to translate mixed Bengali-English speech into English, making it easier for analysis, record-keeping, and using AI in healthcare.

An open-source, AI-driven Social Media Digital Twin powered by LLMs (Ollama, vLLM) for Computational Social Science simulations, network analysis, and human-agent interaction.

Synthetic data for fine tuning LLM

Turn documents into high-quality instruction datasets with grounding, quality filtering, deduplication, and provenance.

Generate multi-speaker conversational datasets for LLM fine-tuning. N-persona support, topic variation, conversation continuation, creative briefs with web search, character pools, Docker support. ShareGPT format with configurable role mapping.