spaCy/website/docs/api/cli.jade

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//- 💫 DOCS > USAGE > COMMAND LINE INTERFACE
include ../../_includes/_mixins
p
| As of v1.7.0, spaCy comes with new command line helpers to download and
| link models and show useful debugging information. For a list of available
| commands, type #[code python -m spacy --help].
+aside("Why python -m?")
| The problem with a global entry point is that it's resolved by looking up
| entries in your #[code PATH] environment variable. This can give you
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| unexpected results, like executing the wrong spaCy installation
| (especially when using #[code virtualenv]). #[code python -m] prevents
| fallbacks to system modules and makes sure the correct spaCy version is
| used. If you hate typing it every time, we recommend creating an
| #[code alias] instead.
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+h(2, "download") Download
p
| Download #[+a("/docs/usage/models") models] for spaCy. The downloader finds the
| best-matching compatible version, uses pip to download the model as a
| package and automatically creates a
| #[+a("/docs/usage/models#usage") shortcut link] to load the model by name.
| Direct downloads don't perform any compatibility checks and require the
| model name to be specified with its version (e.g., #[code en_core_web_sm-1.2.0]).
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+code(false, "bash").
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python -m spacy download [model] [--direct]
+table(["Argument", "Type", "Description"])
+row
+cell #[code model]
+cell positional
+cell Model name or shortcut (#[code en], #[code de], #[code vectors]).
+row
+cell #[code --direct], #[code -d]
+cell flag
+cell Force direct download of exact model version.
+row
+cell #[code --help], #[code -h]
+cell flag
+cell Show help message and available arguments.
+infobox("Important note")
| The #[code download] command is mostly intended as a convenient,
| interactive wrapper it performs compatibility checks and prints
| detailed messages in case things go wrong. It's #[strong not recommended]
| to use this command as part of an automated process. If you know which
| model your project needs, you should consider a
| #[+a("/docs/usage/models#download-pip") direct download via pip], or
| uploading the model to a local PyPi installation and fetching it straight
| from there. This will also allow you to add it as a versioned package
| dependency to your project.
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+h(2, "link") Link
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| Create a #[+a("/docs/usage/models#usage") shortcut link] for a model,
| either a Python package or a local directory. This will let you load
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| models from any location using a custom name via
| #[+api("spacy#load") #[code spacy.load()]].
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+code(false, "bash").
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python -m spacy link [origin] [link_name] [--force]
+table(["Argument", "Type", "Description"])
+row
+cell #[code origin]
+cell positional
+cell Model name if package, or path to local directory.
+row
+cell #[code link_name]
+cell positional
+cell Name of the shortcut link to create.
+row
+cell #[code --force], #[code -f]
+cell flag
+cell Force overwriting of existing link.
+row
+cell #[code --help], #[code -h]
+cell flag
+cell Show help message and available arguments.
+h(2, "info") Info
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| Print information about your spaCy installation, models and local setup,
| and generate #[+a("https://en.wikipedia.org/wiki/Markdown") Markdown]-formatted
| markup to copy-paste into #[+a(gh("spacy") + "/issues") GitHub issues].
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+code(false, "bash").
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python -m spacy info [--markdown]
python -m spacy info [model] [--markdown]
+table(["Argument", "Type", "Description"])
+row
+cell #[code model]
+cell positional
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+cell A model, i.e. shortcut link, package name or path (optional).
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+row
+cell #[code --markdown], #[code -md]
+cell flag
+cell Print information as Markdown.
+row
+cell #[code --help], #[code -h]
+cell flag
+cell Show help message and available arguments.
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+h(2, "convert") Convert
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+tag experimental
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| Convert files into spaCy's #[+a("/docs/api/annotation#json-input") JSON format]
| for use with the #[code train] command and other experiment management
| functions. The right converter is chosen based on the file extension of
| the input file. Currently only supports #[code .conllu].
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+code(false, "bash").
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python -m spacy convert [input_file] [output_dir] [--n-sents] [--morphology]
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+table(["Argument", "Type", "Description"])
+row
+cell #[code input_file]
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+cell positional
+cell Input file.
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+row
+cell #[code output_dir]
+cell positional
+cell Output directory for converted JSON file.
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+row
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+cell #[code --n-sents], #[code -n]
+cell option
+cell Number of sentences per document.
+row
+cell #[code --morphology], #[code -m]
+cell option
+cell Enable appending morphology to tags.
+row
+cell #[code --help], #[code -h]
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+cell flag
+cell Show help message and available arguments.
+h(2, "model") Model
+tag experimental
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| Initialise a new model and its data directory. For more info on this, see
| the documentation on #[+a("/docs/usage/adding-languages") adding languages].
+code(false, "bash").
python -m spacy model [lang] [model_dir] [freqs_data] [clusters_data] [vectors_data]
+table(["Argument", "Type", "Description"])
+row
+cell #[code lang]
+cell positional
+cell Model language.
+row
+cell #[code model_dir]
+cell positional
+cell Output directory to store the model in.
+row
+cell #[code freqs_data]
+cell positional
+cell Tab-separated frequencies file.
+row
+cell #[code clusters_data]
+cell positional
+cell Brown custers file (optional).
+row
+cell #[code vectors_data]
+cell positional
+cell Word vectors file (optional).
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+row
+cell #[code --help], #[code -h]
+cell flag
+cell Show help message and available arguments.
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+h(2, "train") Train
+tag experimental
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| Train a model. Expects data in spaCy's
| #[+a("/docs/api/annotation#json-input") JSON format].
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+code(false, "bash").
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python -m spacy train [lang] [output_dir] [train_data] [dev_data] [--n-iter] [--parser-L1] [--no-tagger] [--no-parser] [--no-ner]
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+table(["Argument", "Type", "Description"])
+row
+cell #[code lang]
+cell positional
+cell Model language.
+row
+cell #[code output_dir]
+cell positional
+cell Directory to store model in.
+row
+cell #[code train_data]
+cell positional
+cell Location of JSON-formatted training data.
+row
+cell #[code dev_data]
+cell positional
+cell Location of JSON-formatted dev data (optional).
+row
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+cell #[code --n-iter], #[code -n]
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+cell option
+cell Number of iterations (default: #[code 15]).
+row
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+cell #[code --nsents]
+cell option
+cell Number of sentences (default: #[code 0]).
+row
+cell #[code --parser-L1], #[code -L]
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+cell option
+cell L1 regularization penalty for parser (default: #[code 0.0]).
+row
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+cell #[code --use-gpu], #[code -g]
+cell flag
+cell Use GPU.
+row
+cell #[code --no-tagger], #[code -T]
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+cell flag
+cell Don't train tagger.
+row
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+cell #[code --no-parser], #[code -P]
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+cell flag
+cell Don't train parser.
+row
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+cell #[code --no-ner], #[code -N]
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+cell flag
+cell Don't train NER.
+row
+cell #[code --help], #[code -h]
+cell flag
+cell Show help message and available arguments.
+h(2, "package") Package
+tag experimental
p
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| Generate a #[+a("/docs/usage/saving-loading#generating") model Python package]
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| from an existing model data directory. All data files are copied over.
| If the path to a meta.json is supplied, or a meta.json is found in the
| input directory, this file is used. Otherwise, the data can be entered
| directly from the command line. While this feature is still experimental,
| the required file templates are downloaded from
| #[+src(gh("spacy-dev-resources", "templates/model")) GitHub]. This means
| you need to be connected to the internet to use this command.
+code(false, "bash").
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python -m spacy package [input_dir] [output_dir] [--meta] [--force]
+table(["Argument", "Type", "Description"])
+row
+cell #[code input_dir]
+cell positional
+cell Path to directory containing model data.
+row
+cell #[code output_dir]
+cell positional
+cell Directory to create package folder in.
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+row
+cell #[code meta]
+cell option
+cell Path to meta.json file (optional).
+row
+cell #[code --force], #[code -f]
+cell flag
+cell Force overwriting of existing folder in output directory.
+row
+cell #[code --help], #[code -h]
+cell flag
+cell Show help message and available arguments.