mirror of https://github.com/explosion/spaCy.git
b71a11ff6d
* Add pos and morph scoring to Scorer Add pos, morph, and morph_per_type to `Scorer`. Report pos and morph accuracy in `spacy evaluate`. * Update morphologizer for v3 * switch to tagger-based morphologizer * use `spacy.HashCharEmbedCNN` for morphologizer defaults * add `Doc.is_morphed` flag * Add morphologizer to train CLI * Add basic morphologizer pipeline tests * Add simple morphologizer training example * Remove subword_features from CharEmbed models Remove `subword_features` argument from `spacy.HashCharEmbedCNN.v1` and `spacy.HashCharEmbedBiLSTM.v1` since in these cases `subword_features` is always `False`. * Rename setting in morphologizer example Use `with_pos_tags` instead of `without_pos_tags`. * Fix kwargs for spacy.HashCharEmbedBiLSTM.v1 * Remove defaults for spacy.HashCharEmbedBiLSTM.v1 Remove default `nM/nC` for `spacy.HashCharEmbedBiLSTM.v1`. * Set random seed for textcat overfitting test |
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| experiments | ||
| information_extraction | ||
| keras_parikh_entailment | ||
| notebooks | ||
| pipeline | ||
| training | ||
| README.md | ||
| deep_learning_keras.py | ||
| load_from_docbin.py | ||
| streamlit_spacy.py | ||
| vectors_fast_text.py | ||
| vectors_tensorboard.py | ||
README.md
spaCy examples
The examples are Python scripts with well-behaved command line interfaces. For more detailed usage guides, see the documentation.
To see the available arguments, you can use the --help or -h flag:
$ python examples/training/train_ner.py --help
While we try to keep the examples up to date, they are not currently exercised by the test suite, as some of them require significant data downloads or take time to train. If you find that an example is no longer running, please tell us! We know there's nothing worse than trying to figure out what you're doing wrong, and it turns out your code was never the problem.