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