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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

Synthetic data models supported by Gretel APIs.
  • Gretel ACTGAN - Adversarial model for tabular, structured numerical, high column count data.
  • Gretel Tabular DP - Graph-based model for tabular data with differential privacy.
  • Gretel GPT - Generative pre-trained transformer for natural language text.
  • Gretel DGAN - Adversarial model for time-series data.
  • Gretel Amplify - Statistical model for high volume tabular data.
  • Gretel LSTM - Language model for tabular, time series, text data.

Supported Features

This section compares features of different generative data models supported by Gretel APIs.
✅ = Supported
✖️ = Not yet supported
LSTM
ACTGAN
Amplify
DGAN
GPT
Tabular DP
Tag
synthetics
actgan
amplify
timeseries_dgan
gpt_x
tabular_dp
Type
Language Model
Generative Adversarial Network
Statistical
Generative Adversarial Network
Language Model
Statistical
Model
LSTM
GAN
Statistical
GAN
Pre-trained Transformer
Probabilistic Graphical Model
Privacy filters
✖️
✖️
✖️
Differential privacy
✖️
✖️
✖️
✖️
✖️
✖️
Tabular
✖️
Time-series
✖️
✖️
✖️
✖️
Natural language
✖️
✖️
✖️
✖️
Conditional generation
✖️
✖️
Pre-trained
✖️
✖️
✖️
✖️
✖️
Gretel cloud
Hybrid cloud
Requires GPU
✖️
✖️
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.