How can I save a final model after training it on chunks of data?
One option is Dask framework's incremental learning. That would automate the loading of chunks and applying partial_fit in scikit-learn.
The code would be something like:
from dask_ml.datasets import make_classification
from dask_ml.wrappers import Incremental

X, y = make_classification(chunks=25)
estimator = LinearSVC(random_state=10, max_iter=100)
clf = Incremental(estimator)
clf.fit(X, y, classes=[0, 1])

joblib.dump(clf, filename)