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View Code? Open in Web Editor NEW๐พ A lightweight & extensible library to create complex multi-model and multi-modal pipelines, including ``Ensembles`` and ``Meta-Models``
License: Other
๐พ A lightweight & extensible library to create complex multi-model and multi-modal pipelines, including ``Ensembles`` and ``Meta-Models``
License: Other
save:bool
- switch off all model saving
save_remote:bool
- switch off all model remote saving
wandb_loging:bool
train:bool
- train or test
(?) run_name:str
- expclitly specify run name or append to pipeline.id
force_fit:bool
- weather all models should force fit
Provide a variety of metrics, for classification right now only. Save the stats.
Take any of the over/undersampling functions from this libraryhttps://imbalanced-learn.org/
with a single function, download & potentially convert any HF dataset into what we need, store it in a separate directory.
Train on different datasets, on a different objective, then use those models to predict emotion/sentiment/etc. and train a meta-model on their output
http://www.sce.carleton.ca/faculty/green/papers/MetaModel_poster_AL_DK.pdf
Giving an interface for features to be developed.
Baseline, individual models:
Ensemble:
get the plotting function from https://pypi.org/project/pycaleva/
also, save the returned plots!
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