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Models

This section covers the generative machine learning models supported by Gretel APIs as well as core use cases and capabilities.

Synthetic Models

Gretel currently has five synthetic models, with more models and supported datatypes coming soon.
  • Gretel LSTM - deep learning model that supports tabular, time-series, and natural language text data.
  • Gretel ACTGAN - adversarial model that supports tabular data, structured numerical data, and high column count data.
  • Gretel Amplify - statistical model that supports high volumes of tabular data generation.
  • Gretel DGAN - adversarial model for time series data.
  • Gretel GPT - generative pre-trained transformer for natural language text generation.

Supported Features

This section compares features of different generative data models supported by Gretel APIs.
✅ = Supported
✖️ = Not yet supported
LSTM
ACTGAN
Amplify
DGAN
GPT
Tag
synthetics
actgan
amplify
timeseries_dgan
gpt_x
Type
Language Model
Generative Adversarial Network
Statistical
Generative Adversarial Network
Language Model
Model
LSTM
GAN
Statistical
GAN
Pre-trained Transformer
Privacy filters
✖️
✖️
Differential privacy
✖️
✖️
✖️
✖️
Synthetic quality report
✖️
✖️
Tabular
✖️
Time-series
✖️
✖️
✖️
Natural language
✖️
✖️
✖️
Conditional generation
✖️
Pre-trained
✖️
✖️
✖️
✖️
Gretel cloud
Hybrid cloud
GitHub - gretelai/gretel-synthetics: Synthetic data generators for structured and unstructured text, featuring differentially private learning.
GitHub
Check out our GitHub for research, source code and examples including our core synthetic data generation library.