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Update download docs [ci skip]
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Ines Montani
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@ -23,11 +23,11 @@ type `spacy --help`.
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## Download {#download}
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Download [models](/usage/models) for spaCy. The downloader finds the
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best-matching compatible version, uses pip to download the model as a package
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and automatically creates a [shortcut link](/usage/models#usage) to load the
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model by name. Direct downloads don't perform any compatibility checks and
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require the model name to be specified with its version (e.g.
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`en_core_web_sm-2.0.0`).
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best-matching compatible version, uses `pip install` to download the model as a
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package and creates a [shortcut link](/usage/models#usage) if the model was
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downloaded via a shortcut. Direct downloads don't perform any compatibility
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checks and require the model name to be specified with its version (e.g.
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`en_core_web_sm-2.2.0`).
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> #### Downloading best practices
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>
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@ -40,16 +40,16 @@ require the model name to be specified with its version (e.g.
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> also allow you to add it as a versioned package dependency to your project.
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```bash
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$ python -m spacy download [model] [--direct]
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$ python -m spacy download [model] [--direct] [pip args]
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```
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| Argument | Type | Description |
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| ---------------------------------- | ------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `model` | positional | Model name or shortcut (`en`, `de`, `en_core_web_sm`). |
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| `--direct`, `-d` | flag | Force direct download of exact model version. |
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| other <Tag variant="new">2.1</Tag> | - | Additional installation options to be passed to `pip install` when installing the model package. For example, `--user` to install to the user home directory. |
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| `--help`, `-h` | flag | Show help message and available arguments. |
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| **CREATES** | directory, symlink | The installed model package in your `site-packages` directory and a shortcut link as a symlink in `spacy/data`. |
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| Argument | Type | Description |
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| ------------------------------------- | ------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `model` | positional | Model name or shortcut (`en`, `de`, `en_core_web_sm`). |
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| `--direct`, `-d` | flag | Force direct download of exact model version. |
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| pip args <Tag variant="new">2.1</Tag> | - | Additional installation options to be passed to `pip install` when installing the model package. For example, `--user` to install to the user home directory or `--no-deps` to not install model dependencies. |
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| `--help`, `-h` | flag | Show help message and available arguments. |
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| **CREATES** | directory, symlink | The installed model package in your `site-packages` directory and a shortcut link as a symlink in `spacy/data` if installed via shortcut. |
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## Link {#link}
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@ -368,33 +368,33 @@ $ python -m spacy train [lang] [output_path] [train_path] [dev_path]
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[--verbose]
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```
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| Argument | Type | Description |
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| ----------------------------------------------------- | ------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `lang` | positional | Model language. |
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| `output_path` | positional | Directory to store model in. Will be created if it doesn't exist. |
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| `train_path` | positional | Location of JSON-formatted training data. Can be a file or a directory of files. |
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| `dev_path` | positional | Location of JSON-formatted development data for evaluation. Can be a file or a directory of files. |
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| `--base-model`, `-b` <Tag variant="new">2.1</Tag> | option | Optional name of base model to update. Can be any loadable spaCy model. |
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| `--pipeline`, `-p` <Tag variant="new">2.1</Tag> | option | Comma-separated names of pipeline components to train. Defaults to `'tagger,parser,ner'`. |
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| `--vectors`, `-v` | option | Model to load vectors from. |
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| `--n-iter`, `-n` | option | Number of iterations (default: `30`). |
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| `--n-early-stopping`, `-ne` | option | Maximum number of training epochs without dev accuracy improvement. |
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| `--n-examples`, `-ns` | option | Number of examples to use (defaults to `0` for all examples). |
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| `--use-gpu`, `-g` | option | Whether to use GPU. Can be either `0`, `1` or `-1`. |
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| `--version`, `-V` | option | Model version. Will be written out to the model's `meta.json` after training. |
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| `--meta-path`, `-m` <Tag variant="new">2</Tag> | option | Optional path to model [`meta.json`](/usage/training#models-generating). All relevant properties like `lang`, `pipeline` and `spacy_version` will be overwritten. |
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| `--init-tok2vec`, `-t2v` <Tag variant="new">2.1</Tag> | option | Path to pretrained weights for the token-to-vector parts of the models. See `spacy pretrain`. Experimental. |
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| `--parser-multitasks`, `-pt` | option | Side objectives for parser CNN, e.g. `'dep'` or `'dep,tag'` |
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| `--entity-multitasks`, `-et` | option | Side objectives for NER CNN, e.g. `'dep'` or `'dep,tag'` |
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| `--noise-level`, `-nl` | option | Float indicating the amount of corruption for data augmentation. |
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| `--gold-preproc`, `-G` | flag | Use gold preprocessing. |
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| `--learn-tokens`, `-T` | flag | Make parser learn gold-standard tokenization by merging ] subtokens. Typically used for languages like Chinese. |
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| `--textcat-multilabel`, `-TML` <Tag variant="new">2.2</Tag> | flag | Text classification classes aren't mutually exclusive (multilabel). |
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| `--textcat-arch`, `-ta` <Tag variant="new">2.2</Tag> | option | Text classification model architecture. Defaults to `"bow"`. |
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| `--textcat-positive-label`, `-tpl` <Tag variant="new">2.2</Tag> | option |Text classification positive label for binary classes with two labels. |
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| `--verbose`, `-VV` <Tag variant="new">2.0.13</Tag> | flag | Show more detailed messages during training. |
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| `--help`, `-h` | flag | Show help message and available arguments. |
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| **CREATES** | model, pickle | A spaCy model on each epoch. |
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| Argument | Type | Description |
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| --------------------------------------------------------------- | ------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `lang` | positional | Model language. |
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| `output_path` | positional | Directory to store model in. Will be created if it doesn't exist. |
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| `train_path` | positional | Location of JSON-formatted training data. Can be a file or a directory of files. |
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| `dev_path` | positional | Location of JSON-formatted development data for evaluation. Can be a file or a directory of files. |
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| `--base-model`, `-b` <Tag variant="new">2.1</Tag> | option | Optional name of base model to update. Can be any loadable spaCy model. |
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| `--pipeline`, `-p` <Tag variant="new">2.1</Tag> | option | Comma-separated names of pipeline components to train. Defaults to `'tagger,parser,ner'`. |
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| `--vectors`, `-v` | option | Model to load vectors from. |
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| `--n-iter`, `-n` | option | Number of iterations (default: `30`). |
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| `--n-early-stopping`, `-ne` | option | Maximum number of training epochs without dev accuracy improvement. |
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| `--n-examples`, `-ns` | option | Number of examples to use (defaults to `0` for all examples). |
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| `--use-gpu`, `-g` | option | Whether to use GPU. Can be either `0`, `1` or `-1`. |
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| `--version`, `-V` | option | Model version. Will be written out to the model's `meta.json` after training. |
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| `--meta-path`, `-m` <Tag variant="new">2</Tag> | option | Optional path to model [`meta.json`](/usage/training#models-generating). All relevant properties like `lang`, `pipeline` and `spacy_version` will be overwritten. |
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| `--init-tok2vec`, `-t2v` <Tag variant="new">2.1</Tag> | option | Path to pretrained weights for the token-to-vector parts of the models. See `spacy pretrain`. Experimental. |
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| `--parser-multitasks`, `-pt` | option | Side objectives for parser CNN, e.g. `'dep'` or `'dep,tag'` |
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| `--entity-multitasks`, `-et` | option | Side objectives for NER CNN, e.g. `'dep'` or `'dep,tag'` |
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| `--noise-level`, `-nl` | option | Float indicating the amount of corruption for data augmentation. |
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| `--gold-preproc`, `-G` | flag | Use gold preprocessing. |
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| `--learn-tokens`, `-T` | flag | Make parser learn gold-standard tokenization by merging ] subtokens. Typically used for languages like Chinese. |
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| `--textcat-multilabel`, `-TML` <Tag variant="new">2.2</Tag> | flag | Text classification classes aren't mutually exclusive (multilabel). |
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| `--textcat-arch`, `-ta` <Tag variant="new">2.2</Tag> | option | Text classification model architecture. Defaults to `"bow"`. |
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| `--textcat-positive-label`, `-tpl` <Tag variant="new">2.2</Tag> | option | Text classification positive label for binary classes with two labels. |
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| `--verbose`, `-VV` <Tag variant="new">2.0.13</Tag> | flag | Show more detailed messages during training. |
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| `--help`, `-h` | flag | Show help message and available arguments. |
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| **CREATES** | model, pickle | A spaCy model on each epoch. |
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### Environment variables for hyperparameters {#train-hyperparams new="2"}
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