Alternatives and similar repositories for awesome-synthetic-data:

Users that are interested in awesome-synthetic-data are comparing it to the libraries listed below

• statice / awesome-synthetic-data
  A curated list of awesome synthetic data tools (open source and commercial).
  ☆162Updated last year
• gretelai / GAN-location-generator
  Use FastCUT with public map images and location data from a few cities to generate realistic synthetic location data for any city in the …
  ☆23Updated 3 years ago
• gretelai / trainer
  Simple interface to synthesize complex and highly dimensional datasets using Gretel APIs.
  ☆29Updated 3 weeks ago
• joofio / awesome-data-synthesis
  A curated list of awesome resources for creating synthetic data
  ☆42Updated 3 years ago
• NextBrain-ai / nbsynthetic
  nbsynthetic is simple and robust tabular synthetic data generation library for small and medium size datasets
  ☆65Updated 2 years ago
• gretelai / gretel-python-client
  The Gretel Python Client allows you to interact with the Gretel REST API.
  ☆53Updated this week
• gretelai / public_research
  Where Gretel published notebooks and code for blog posts
  ☆19Updated last year
• worldbank / REaLTabFormer
  A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.
  ☆223Updated 2 weeks ago
• stanford-crfm / EUAIActJune15
  Stanford CRFM's initiative to assess potential compliance with the draft EU AI Act
  ☆93Updated last year
• gretelai / gdpr-helpers
  Generative models to automatically anonymize data to meet GDPR & CCPA standards.
  ☆31Updated 2 years ago
• sdv-dev / SDMetrics
  Metrics to evaluate quality and efficacy of synthetic datasets.
  ☆228Updated this week
• gretelai / gretel-blueprints
  Public blueprints for data use cases
  ☆74Updated this week
• fiddler-labs / fiddler-auditor
  Fiddler Auditor is a tool to evaluate language models.
  ☆176Updated last year
• Data-Centric-AI-Community / nist-crc-2023
  NIST Collaborative Research Cycle on Synthetic Data. Learn about Synthetic Data week by week!
  ☆27Updated last year
• sdv-dev / RDT
  A library of Reversible Data Transforms
  ☆124Updated this week
• HazyResearch / fm_data_tasks
  Foundation Models for Data Tasks
  ☆103Updated last year
• DataResponsibly / MirrorDataGenerator
  MirrorDataGenerator is a python tool that generates synthetic data based on user-specified causal relations among features in the data. I…
  ☆21Updated 2 years ago
• gretelai / gretel-synthetics
  Synthetic data generators for structured and unstructured text, featuring differentially private learning.
  ☆618Updated last week
• davanstrien / data-for-fine-tuning-llms
  ☆76Updated 9 months ago
• mkuchnik / relm
  ReLM is a Regular Expression engine for Language Models
  ☆103Updated last year
• facebookresearch / synlm
  Code for paper: "Privately generating tabular data using language models".
  ☆15Updated last year
• jongjyh / TrFr
  Truth Forest: Toward Multi-Scale Truthfulness in Large Language Models through Intervention without Tuning
  ☆46Updated last year
• mlfoundations / rtfm
  Research on Tabular Foundation Models
  ☆43Updated 3 months ago
• withmartian / routerbench
  The code for the paper ROUTERBENCH: A Benchmark for Multi-LLM Routing System
  ☆109Updated 9 months ago
• kathrinse / be_great
  A novel approach for synthesizing tabular data using pretrained large language models
  ☆303Updated 4 months ago
• noahho / CAAFE
  Semi-automatic feature engineering process using Language Models and your dataset descriptions. Based on the paper "LLMs for Semi-Automat…
  ☆155Updated 3 months ago
• microsoft / DPSDA
  Private Evolution: Generating DP Synthetic Data without Training [ICLR 2024, ICML 2024 Spotlight]
  ☆91Updated last month
• stanford-crfm / ecosystem-graphs
  ☆263Updated 2 months ago
• IFCA-Advanced-Computing / pycanon
  pyCANON is a Python library and CLI to assess the values of the parameters associated with the most common privacy-preserving techniques.
  ☆35Updated this week
• santiviquez / ageml
  Study the temporal performance degradation of machine learning models.
  ☆15Updated last year