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	Fix documentation API
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				|  | @ -64,12 +64,11 @@ architectures and their arguments and hyperparameters. | |||
| > #### Example (spancat_exclusive) | ||||
| > | ||||
| > ```python | ||||
| > from spacy.pipeline.spancat import DEFAULT_SPANCAT_MODEL | ||||
| > from spacy.pipeline.spancat_exclusive import DEFAULT_EXCL_SPANCAT_MODEL | ||||
| > config = { | ||||
| >     "threshold": 0.5, | ||||
| >     "spans_key": "labeled_spans", | ||||
| >     "max_positive": None, | ||||
| >     "model": DEFAULT_SPANCAT_MODEL, | ||||
| >     "model": DEFAULT_EXCL_SPANCAT_MODEL, | ||||
| >     "suggester": {"@misc": "spacy.ngram_suggester.v1", "sizes": [1, 2, 3]}, | ||||
| >     # Additional spancat_exclusive parameters | ||||
| >     "negative_weight": 1.0, | ||||
|  | @ -85,7 +84,7 @@ architectures and their arguments and hyperparameters. | |||
| | `model`        | A model instance that is given a a list of documents and `(start, end)` indices representing candidate span offsets. The model predicts a probability for each category for each span. Defaults to [SpanCategorizer](/api/architectures#SpanCategorizer). ~~Model[Tuple[List[Doc], Ragged], Floats2d]~~ | | ||||
| | `spans_key`    | Key of the [`Doc.spans`](/api/doc#spans) dict to save the spans under. During initialization and training, the component will look for spans on the reference document under the same key. Defaults to `"sc"`. ~~str~~                                                                                  | | ||||
| | `threshold`    | Minimum probability to consider a prediction positive. Spans with a positive prediction will be saved on the Doc. Defaults to `0.5`. ~~float~~                                                                                                                                                          | | ||||
| | `max_positive` | Maximum number of labels to consider positive per span. Defaults to `None`, indicating no limit. ~~Optional[int]~~                                                                                                                                                                                      | | ||||
| | `max_positive` | Maximum number of labels to consider positive per span. Defaults to `None`, indicating no limit. It is only available for the `spancat` component. ~~Optional[int]~~                                                                                                                                                                                      | | ||||
| | `scorer`       | The scoring method. Defaults to [`Scorer.score_spans`](/api/scorer#score_spans) for `Doc.spans[spans_key]` with overlapping spans allowed. ~~Optional[Callable]~~                                                                                                                                       | | ||||
| | `negative_weight`    | Multiplier for the loss terms. It can be used to downweight the negative samples if there are too many. It is only available for the `spancat_exclusive` component. ~~float~~                                                  | | ||||
| | `allow_overlap`        | If `True`, the data is assumed to contain overlapping spans. It is only available for the `spancat_exclusive` component. ~~bool~~ | | ||||
|  |  | |||
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