NER with IOB/IOB2/BILUO tags, one token per line with columns separated by whitespace. JSON-formatted training data used in spaCy v2.x. Optional (option)Ĭoncatenate output to a single file bool (flag)īinary DocBin training data that can be used with spacy train.Īutomatically pick converter based on file extension and file content (default). NER tag mapping (as JSON-encoded dict of entity types). Optional (option)Įnable appending morphology to tags. Trained spaCy pipeline for sentence segmentation to use as base (for -seg-sents). Supported for: conll, conllu, iob, ner int (option) Either spacy (default) for binary DocBin data or json for v2.x JSON format. Defaults to "-", meaning data will be written to stdout. The converter can be specified on the command line, orĬhosen based on the file extension of the input file. Any (option/flag)īinary training data format, a serializedĭocBin, for use with the train command and other experiment Should be options starting with - that correspond to the config section and value to override, e.g. int (option)Ĭonfig parameters to override. Show more detailed messages for debugging purposes. Allows registering custom functions for new architectures. Path to Python file with additional code to be imported. Path to training config file containing all settings and hyperparameters. Labels argument on initialization via the Process, since spaCy won’t have to preprocess the data to extract the labels.Īfter generating the labels, you can provide them to components that accept a Generate JSON files for the labels in the data. bool (flag)Ī spaCy pipeline directory containing the vocab and vectors. Print additional information and explanations. Name to assign to the word vectors in the meta.json, e.g. Number of vectors to prune the vocabulary to. Number of vectors to truncate to when reading in vectors file. Should be a file where the first row contains the dimensions of the vectors, followed by a space-separated Word2Vec table. Pipeline language IETF language tag, such as en. This functionality was previously available as part of the command init-model. If your configĬontains a problem that can’t be resolved automatically, spaCy will show you a The available settings and defaults, all functions referenced in the config willīe created, and their signatures are used to find the defaults. So this command helps you create your final training config. Should always be complete and not contain any hidden defaults or missing values, bool (flag)įorce overwriting the output file if it already exists. Include config for pretraining (with spacy pretrain). This will impact the choice of architecture, pretrained weights and related hyperparameters. Whether to optimize for efficiency (faster inference, smaller model, lower memory consumption) or higher accuracy (potentially larger and slower model). str (option)Ĭomma-separated list of trainable pipeline components to include. Note that if you’re writing to stdout, no additional logging info is printed. cfg file or - to write the config to stdout (so you can pipe it forward to a file or to the train command). If any package is out of date, the latestĬompatible versions and command for updating are shown. Should be run after upgrading spaCy via pip install -U spacy to ensure thatĪll installed packages can be used with the new version. Information about your spaCy installation.įind all trained pipeline packages installed in the current environment andĬheck whether they are compatible with the currently installed version of spaCy. Print the URL to download the most recent compatible version of the pipeline. bool (flag)Ĭomma-separated keys to exclude from the print-out. bool (flag)ĭon’t print anything, just return the values. Print information about your spaCy installation, trained pipelines and localĪ trained pipeline, i.e. The installed pipeline package in your site-packages directory. For example, -user to install to the user home directory or -no-deps to not install package dependencies. bool (flag)Īdditional installation options to be passed to pip install when installing the pipeline package. Show help message and available arguments. tar.gz archive) instead of the default pre-built binary wheel. bool (flag)ĭownload the source package (. str (positional)įorce direct download of exact package version. Will also allow you to add it as a versioned package dependency to your Package to a local PyPi installation and fetching it straight from there. If you know which package your project needs, you should consider aĭirect download via pip, or uploading the It’s not recommended to use this command as part of an automated – it performs compatibility checks and prints detailed messages in case things The download command is mostly intended as a convenient, interactive wrapper
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