A minimal demo parser project for spaCy v3 adapted from the spaCy v2 train_parser.py
example script.
The project.yml
defines the data assets required by the
project, as well as the available commands and workflows. For details, see the
spaCy projects documentation.
The following commands are defined by the project. They
can be executed using spacy project run [name]
.
Commands are only re-run if their inputs have changed.
Command | Description |
---|---|
download |
Download a spaCy model with pretrained vectors |
convert |
Convert the data to spaCy's binary format |
create-config |
Create a new config with a parser pipeline component |
train |
Train the parser model |
train-with-vectors |
Train the parser model with vectors |
evaluate |
Evaluate the model and export metrics |
package |
Package the trained model as a pip package |
visualize-model |
Visualize the model's output interactively using Streamlit |
The following workflows are defined by the project. They
can be executed using spacy project run [name]
and will run the specified commands in order. Commands are only re-run if their
inputs have changed.
Workflow | Steps |
---|---|
all |
convert → create-config → train → evaluate |
The following assets are defined by the project. They can
be fetched by running spacy project assets
in the project directory.
File | Source | Description |
---|---|---|
assets/train.json |
Local | Demo training data converted from the v2 train_parser.py example with srsly.write_json("train.json", TRAIN_DATA) |
assets/dev.json |
Local | Demo development data |