0.3.4
This release is a big design change and refactor. It involves a significant change in the Configuration file structure, meaning this is a breaking upgrade.
For those upgrading from an older version of ZenML, we ask to please delete their old pipelines
dir and .zenml
folders and start afresh with a zenml init
.
If only working locally, this is as simple as:
cd zenml_enabled_repo
rm -rf pipelines/
rm -rf .zenml/
And then another ZenML init:
pip install --upgrade zenml
cd zenml_enabled_repo
zenml init
New Features
- Introduced another higher-level pipeline: The NLPPipeline. This is a generic
NLP pipeline for a text-datasource based training task. Full example of how to use the NLPPipeline can be found here - Introduced a BaseTokenizerStep as a simple mechanism to define how to train and encode using any generic
tokenizer (again for NLP-based tasks). - Introduced a new HuggingFace integration, with the first concrete implementation of the BaseTokenizerStep, i.e., the HuggingFaceTokenizer.
- Show-cased how to use HuggingFace with the ZenML TrainerStep in the NLP Example.
Bug Fixes + Refactor
- Significant change to imports: Now imports are way simpler and user-friendly. E.g. Instead of:
from zenml.core.pipelines.training_pipeline import TrainingPipeline
A user can simple do:
from zenml.pipelines import TrainingPipeline
The caveat is of course that this might involve a re-write of older ZenML code imports.
Note: Future releases are also expected to be breaking. Until announced, please expect that upgrading ZenML versions may cause older-ZenML generated pipelines to behave unexpectedly.
Special shout-out to @nicholasmaiot for major contributions to this release!