//- 💫 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]. To make the command even more | convenient, we recommend | #[+a("https://askubuntu.com/questions/17536/how-do-i-create-a-permanent-bash-alias/17537#17537") creating an alias] | mapping #[code python -m spacy] to #[code spacy]. +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 | unexpected results, like executing the wrong spaCy installation. | #[code python -m] prevents fallbacks to system modules. +infobox("⚠️ Deprecation note") | As of spaCy 2.0, the #[code model] command to initialise a model data | directory is deprecated. The command was only necessary because previous | versions of spaCy expected a model directory to already be set up. This | has since been changed, so you can use the #[+api("cli#train") #[code train]] | command straight away. +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]). +code(false, "bash"). 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. +aside("Downloading best practices") | 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. +h(2, "link") Link p | 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 | models from any location using a custom name via | #[+api("spacy#load") #[code spacy.load()]]. +code(false, "bash"). 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 p | 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]. +code(false, "bash"). python -m spacy info [--markdown] python -m spacy info [model] [--markdown] +table(["Argument", "Type", "Description"]) +row +cell #[code model] +cell positional +cell A model, i.e. shortcut link, package name or path (optional). +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. +h(2, "convert") Convert p | 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]. +code(false, "bash"). python -m spacy convert [input_file] [output_dir] [--n-sents] [--morphology] +table(["Argument", "Type", "Description"]) +row +cell #[code input_file] +cell positional +cell Input file. +row +cell #[code output_dir] +cell positional +cell Output directory for converted JSON file. +row +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] +cell flag +cell Show help message and available arguments. +h(2, "train") Train p | Train a model. Expects data in spaCy's | #[+a("/docs/api/annotation#json-input") JSON format]. +code(false, "bash"). python -m spacy train [lang] [output_dir] [train_data] [dev_data] [--n-iter] [--n-sents] [--use-gpu] [--no-tagger] [--no-parser] [--no-entities] +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 +cell #[code --n-iter], #[code -n] +cell option +cell Number of iterations (default: #[code 20]). +row +cell #[code --n-sents], #[code -ns] +cell option +cell Number of sentences (default: #[code 0]). +row +cell #[code --use-gpu], #[code -G] +cell flag +cell Use GPU. +row +cell #[code --no-tagger], #[code -T] +cell flag +cell Don't train tagger. +row +cell #[code --no-parser], #[code -P] +cell flag +cell Don't train parser. +row +cell #[code --no-entities], #[code -N] +cell flag +cell Don't train NER. +row +cell #[code --help], #[code -h] +cell flag +cell Show help message and available arguments. +h(3, "train-hyperparams") Environment variables for hyperparameters p | spaCy lets you set hyperparameters for training via environment variables. | This is useful, because it keeps the command simple and allows you to | #[+a("https://askubuntu.com/questions/17536/how-do-i-create-a-permanent-bash-alias/17537#17537") create an alias] | for your custom #[code train] command while still being able to easily | tweak the hyperparameters. For example: +code(false, "bash"). parser_hidden_depth=2 parser_maxout_pieces=2 train-parser +under-construction +table(["Name", "Description", "Default"]) +row +cell #[code dropout_from] +cell +cell #[code 0.2] +row +cell #[code dropout_to] +cell +cell #[code 0.2] +row +cell #[code dropout_decay] +cell +cell #[code 0.0] +row +cell #[code batch_from] +cell +cell #[code 1] +row +cell #[code batch_to] +cell +cell #[code 64] +row +cell #[code batch_compound] +cell +cell #[code 1.001] +row +cell #[code token_vector_width] +cell +cell #[code 128] +row +cell #[code embed_size] +cell +cell #[code 7500] +row +cell #[code parser_maxout_pieces] +cell +cell #[code ] +row +cell #[code parser_hidden_depth] +cell +cell #[code ] +row +cell #[code hidden_width] +cell +cell #[code 128] +row +cell #[code learn_rate] +cell +cell #[code 0.001] +row +cell #[code optimizer_B1] +cell +cell #[code 0.9] +row +cell #[code optimizer_B2] +cell +cell #[code 0.999] +row +cell #[code optimizer_eps] +cell +cell #[code 1e-08] +row +cell #[code L2_penalty] +cell +cell #[code 1e-06] +row +cell #[code grad_norm_clip] +cell +cell #[code 1.0] +h(2, "package") Package p | Generate a #[+a("/docs/usage/saving-loading#generating") model Python package] | 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. The required file templates are downloaded | from #[+src(gh("spacy-dev-resources", "templates/model")) GitHub] to make | sure you're always using the latest versions. This means you need to be | connected to the internet to use this command. +code(false, "bash"). 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. +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.