mirror of https://github.com/explosion/spaCy.git
Adjust more arguments [ci skip]
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@ -44,7 +44,7 @@ def convert_cli(
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file_type: FileTypes = Opt("spacy", "--file-type", "-t", help="Type of data to produce"),
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n_sents: int = Opt(1, "--n-sents", "-n", help="Number of sentences per doc (0 to disable)"),
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seg_sents: bool = Opt(False, "--seg-sents", "-s", help="Segment sentences (for -c ner)"),
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model: Optional[str] = Opt(None, "--model", "-b", help="Trained spaCy pipeline for sentence segmentation (for -s)"),
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model: Optional[str] = Opt(None, "--model", "--base", "-b", help="Trained spaCy pipeline for sentence segmentation to use as base (for --seg-sents)"),
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morphology: bool = Opt(False, "--morphology", "-m", help="Enable appending morphology to tags"),
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merge_subtokens: bool = Opt(False, "--merge-subtokens", "-T", help="Merge CoNLL-U subtokens"),
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converter: str = Opt("auto", "--converter", "-c", help=f"Converter: {tuple(CONVERTERS.keys())}"),
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@ -46,8 +46,8 @@ def init_model_cli(
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prune_vectors: int = Opt(-1, "--prune-vectors", "-V", help="Optional number of vectors to prune to"),
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truncate_vectors: int = Opt(0, "--truncate-vectors", "-t", help="Optional number of vectors to truncate to when reading in vectors file"),
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vectors_name: Optional[str] = Opt(None, "--vectors-name", "-vn", help="Optional name for the word vectors, e.g. en_core_web_lg.vectors"),
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model_name: Optional[str] = Opt(None, "--model-name", "-mn", help="Optional name for the pipeline meta"),
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base_model: Optional[str] = Opt(None, "--base-model", "-b", help="Base pipeline (for languages with custom tokenizers)")
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model_name: Optional[str] = Opt(None, "--meta-name", "-mn", help="Optional name of the package for the pipeline meta"),
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base_model: Optional[str] = Opt(None, "--base", "-b", help="Name of or path to base pipeline to start with (mostly relevant for pipelines with custom tokenizers)")
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# fmt: on
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):
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"""
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@ -183,7 +183,7 @@ This command was previously called `init-model`.
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</Infobox>
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```cli
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$ python -m spacy init vocab [lang] [output_dir] [--jsonl-loc] [--vectors-loc] [--prune-vectors]
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$ python -m spacy init vocab [lang] [output_dir] [--jsonl-loc] [--vectors-loc] [--prune-vectors] [--vectors-name] [--meta-name] [--base]
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```
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| Name | Description |
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@ -194,7 +194,9 @@ $ python -m spacy init vocab [lang] [output_dir] [--jsonl-loc] [--vectors-loc] [
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| `--vectors-loc`, `-v` | Optional location of vectors. Should be a file where the first row contains the dimensions of the vectors, followed by a space-separated Word2Vec table. File can be provided in `.txt` format or as a zipped text file in `.zip` or `.tar.gz` format. ~~Optional[Path] \(option)~~ |
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| `--truncate-vectors`, `-t` <Tag variant="new">2.3</Tag> | Number of vectors to truncate to when reading in vectors file. Defaults to `0` for no truncation. ~~int (option)~~ |
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| `--prune-vectors`, `-V` | Number of vectors to prune the vocabulary to. Defaults to `-1` for no pruning. ~~int (option)~~ |
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| `--vectors-name`, `-vn` | Name to assign to the word vectors in the `meta.json`, e.g. `en_core_web_md.vectors`. ~~str (option)~~ |
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| `--vectors-name`, `-vn` | Name to assign to the word vectors in the `meta.json`, e.g. `en_core_web_md.vectors`. ~~Optional[str] \(option)~~ |
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| `--meta-name`, `-mn` | Optional name of the package for the pipeline meta. ~~Optional[str] \(option)~~ |
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| `--base`, `-b` | Optional name of or path to base pipeline to start with (mostly relevant for pipelines with custom tokenizers). ~~Optional[str] \(option)~~ |
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| `--help`, `-h` | Show help message and available arguments. ~~bool (flag)~~ |
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| **CREATES** | A spaCy pipeline directory containing the vocab and vectors. |
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@ -207,7 +209,7 @@ management functions. The converter can be specified on the command line, or
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chosen based on the file extension of the input file.
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```cli
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$ python -m spacy convert [input_file] [output_dir] [--converter] [--file-type] [--n-sents] [--seg-sents] [--model] [--morphology] [--merge-subtokens] [--ner-map] [--lang]
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$ python -m spacy convert [input_file] [output_dir] [--converter] [--file-type] [--n-sents] [--seg-sents] [--base] [--morphology] [--merge-subtokens] [--ner-map] [--lang]
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```
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| Name | Description |
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@ -218,7 +220,7 @@ $ python -m spacy convert [input_file] [output_dir] [--converter] [--file-type]
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| `--file-type`, `-t` <Tag variant="new">2.1</Tag> | Type of file to create. Either `spacy` (default) for binary [`DocBin`](/api/docbin) data or `json` for v2.x JSON format. ~~str (option)~~ |
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| `--n-sents`, `-n` | Number of sentences per document. ~~int (option)~~ |
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| `--seg-sents`, `-s` <Tag variant="new">2.2</Tag> | Segment sentences (for `--converter ner`). ~~bool (flag)~~ |
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| `--model`, `-b` <Tag variant="new">2.2</Tag> | Model for parser-based sentence segmentation (for `--seg-sents`). ~~Optional[str](option)~~ |
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| `--base`, `-b` | Trained spaCy pipeline for sentence segmentation to use as base (for `--seg-sents`). ~~Optional[str](option)~~ |
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| `--morphology`, `-m` | Enable appending morphology to tags. ~~bool (flag)~~ |
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| `--ner-map`, `-nm` | NER tag mapping (as JSON-encoded dict of entity types). ~~Optional[Path](option)~~ |
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| `--lang`, `-l` <Tag variant="new">2.1</Tag> | Language code (if tokenizer required). ~~Optional[str] \(option)~~ |
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