🏫 Supported Models
Ritual ML workflows support hooks for training and inference for most classical models that can be done in Python, such as most scikit-learn models. Some common choices below that can be found from the sklearn library.
|Decision Trees and Random Forests
|sklearn.tree.DecisionTreeClassifier, sklearn.ensemble.RandomForestClassifier sklearn.ensemble.RandomForestRegressor
Ritual ML workflows support inference for open-source models that can be found on any model registry. For seamless user experience, Ritual currently offers optimized support for any large language model with HuggingFace model-ids. It lets users bring their own custom model or use fine-tuned model.
|13b, 30b, 70b
|7b, 40b, 180b
|link oss fine-tuned models
|Your custom model
|Upload your own
Support for text to image and image to image models are coming soon!