mirror of
https://github.com/explosion/spaCy.git
synced 2024-12-25 17:36:30 +03:00
Fix typos in docs (#13466)
* fix typos * prettier formatting --------- Co-authored-by: svlandeg <svlandeg@github.com>
This commit is contained in:
Alex Strick van Linschoten
GitHub
parent
74836524e3
commit
045cd43c3f
|
|
@ -39,7 +39,7 @@ def find_threshold_cli(
|
|||
# fmt: on
|
||||
):
|
||||
"""
|
||||
Runs prediction trials for a trained model with varying tresholds to maximize
|
||||
Runs prediction trials for a trained model with varying thresholds to maximize
|
||||
the specified metric. The search space for the threshold is traversed linearly
|
||||
from 0 to 1 in `n_trials` steps. Results are displayed in a table on `stdout`
|
||||
(the corresponding API call to `spacy.cli.find_threshold.find_threshold()`
|
||||
|
|
@ -81,7 +81,7 @@ def find_threshold(
|
|||
silent: bool = True,
|
||||
) -> Tuple[float, float, Dict[float, float]]:
|
||||
"""
|
||||
Runs prediction trials for models with varying tresholds to maximize the specified metric.
|
||||
Runs prediction trials for models with varying thresholds to maximize the specified metric.
|
||||
model (Union[str, Path]): Pipeline to evaluate. Can be a package or a path to a data directory.
|
||||
data_path (Path): Path to file with DocBin with docs to use for threshold search.
|
||||
pipe_name (str): Name of pipe to examine thresholds for.
|
||||
|
|
|
|||
|
|
@ -329,7 +329,7 @@ def test_language_pipe_error_handler(n_process):
|
|||
nlp.set_error_handler(raise_error)
|
||||
with pytest.raises(ValueError):
|
||||
list(nlp.pipe(texts, n_process=n_process))
|
||||
# set explicitely to ignoring
|
||||
# set explicitly to ignoring
|
||||
nlp.set_error_handler(ignore_error)
|
||||
docs = list(nlp.pipe(texts, n_process=n_process))
|
||||
assert len(docs) == 0
|
||||
|
|
|
|||
|
|
@ -45,33 +45,33 @@ For attributes that represent string values, the internal integer ID is accessed
|
|||
as `Token.attr`, e.g. `token.dep`, while the string value can be retrieved by
|
||||
appending `_` as in `token.dep_`.
|
||||
|
||||
| Attribute | Description |
|
||||
| ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| `DEP` | The token's dependency label. ~~str~~ |
|
||||
| `ENT_ID` | The token's entity ID (`ent_id`). ~~str~~ |
|
||||
| `ENT_IOB` | The IOB part of the token's entity tag. Uses custom integer vaues rather than the string store: unset is `0`, `I` is `1`, `O` is `2`, and `B` is `3`. ~~str~~ |
|
||||
| `ENT_KB_ID` | The token's entity knowledge base ID. ~~str~~ |
|
||||
| `ENT_TYPE` | The token's entity label. ~~str~~ |
|
||||
| `IS_ALPHA` | Token text consists of alphabetic characters. ~~bool~~ |
|
||||
| `IS_ASCII` | Token text consists of ASCII characters. ~~bool~~ |
|
||||
| `IS_DIGIT` | Token text consists of digits. ~~bool~~ |
|
||||
| `IS_LOWER` | Token text is in lowercase. ~~bool~~ |
|
||||
| `IS_PUNCT` | Token is punctuation. ~~bool~~ |
|
||||
| `IS_SPACE` | Token is whitespace. ~~bool~~ |
|
||||
| `IS_STOP` | Token is a stop word. ~~bool~~ |
|
||||
| `IS_TITLE` | Token text is in titlecase. ~~bool~~ |
|
||||
| `IS_UPPER` | Token text is in uppercase. ~~bool~~ |
|
||||
| `LEMMA` | The token's lemma. ~~str~~ |
|
||||
| `LENGTH` | The length of the token text. ~~int~~ |
|
||||
| `LIKE_EMAIL` | Token text resembles an email address. ~~bool~~ |
|
||||
| `LIKE_NUM` | Token text resembles a number. ~~bool~~ |
|
||||
| `LIKE_URL` | Token text resembles a URL. ~~bool~~ |
|
||||
| `LOWER` | The lowercase form of the token text. ~~str~~ |
|
||||
| `MORPH` | The token's morphological analysis. ~~MorphAnalysis~~ |
|
||||
| `NORM` | The normalized form of the token text. ~~str~~ |
|
||||
| `ORTH` | The exact verbatim text of a token. ~~str~~ |
|
||||
| `POS` | The token's universal part of speech (UPOS). ~~str~~ |
|
||||
| `SENT_START` | Token is start of sentence. ~~bool~~ |
|
||||
| `SHAPE` | The token's shape. ~~str~~ |
|
||||
| `SPACY` | Token has a trailing space. ~~bool~~ |
|
||||
| `TAG` | The token's fine-grained part of speech. ~~str~~ |
|
||||
| Attribute | Description |
|
||||
| ------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| `DEP` | The token's dependency label. ~~str~~ |
|
||||
| `ENT_ID` | The token's entity ID (`ent_id`). ~~str~~ |
|
||||
| `ENT_IOB` | The IOB part of the token's entity tag. Uses custom integer values rather than the string store: unset is `0`, `I` is `1`, `O` is `2`, and `B` is `3`. ~~str~~ |
|
||||
| `ENT_KB_ID` | The token's entity knowledge base ID. ~~str~~ |
|
||||
| `ENT_TYPE` | The token's entity label. ~~str~~ |
|
||||
| `IS_ALPHA` | Token text consists of alphabetic characters. ~~bool~~ |
|
||||
| `IS_ASCII` | Token text consists of ASCII characters. ~~bool~~ |
|
||||
| `IS_DIGIT` | Token text consists of digits. ~~bool~~ |
|
||||
| `IS_LOWER` | Token text is in lowercase. ~~bool~~ |
|
||||
| `IS_PUNCT` | Token is punctuation. ~~bool~~ |
|
||||
| `IS_SPACE` | Token is whitespace. ~~bool~~ |
|
||||
| `IS_STOP` | Token is a stop word. ~~bool~~ |
|
||||
| `IS_TITLE` | Token text is in titlecase. ~~bool~~ |
|
||||
| `IS_UPPER` | Token text is in uppercase. ~~bool~~ |
|
||||
| `LEMMA` | The token's lemma. ~~str~~ |
|
||||
| `LENGTH` | The length of the token text. ~~int~~ |
|
||||
| `LIKE_EMAIL` | Token text resembles an email address. ~~bool~~ |
|
||||
| `LIKE_NUM` | Token text resembles a number. ~~bool~~ |
|
||||
| `LIKE_URL` | Token text resembles a URL. ~~bool~~ |
|
||||
| `LOWER` | The lowercase form of the token text. ~~str~~ |
|
||||
| `MORPH` | The token's morphological analysis. ~~MorphAnalysis~~ |
|
||||
| `NORM` | The normalized form of the token text. ~~str~~ |
|
||||
| `ORTH` | The exact verbatim text of a token. ~~str~~ |
|
||||
| `POS` | The token's universal part of speech (UPOS). ~~str~~ |
|
||||
| `SENT_START` | Token is start of sentence. ~~bool~~ |
|
||||
| `SHAPE` | The token's shape. ~~str~~ |
|
||||
| `SPACY` | Token has a trailing space. ~~bool~~ |
|
||||
| `TAG` | The token's fine-grained part of speech. ~~str~~ |
|
||||
|
|
|
|||
|
|
@ -567,7 +567,7 @@ New: 'ORG' (23860), 'PERSON' (21395), 'GPE' (21193), 'DATE' (18080), 'CARDINAL'
|
|||
'LOC' (2113), 'TIME' (1616), 'WORK_OF_ART' (1229), 'QUANTITY' (1150), 'FAC'
|
||||
(1134), 'EVENT' (974), 'PRODUCT' (935), 'LAW' (444), 'LANGUAGE' (338)
|
||||
✔ Good amount of examples for all labels
|
||||
✔ Examples without occurences available for all labels
|
||||
✔ Examples without occurrences available for all labels
|
||||
✔ No entities consisting of or starting/ending with whitespace
|
||||
|
||||
=========================== Part-of-speech Tagging ===========================
|
||||
|
|
@ -1320,7 +1320,7 @@ $ python -m spacy apply [model] [data-path] [output-file] [--code] [--text-key]
|
|||
|
||||
## find-threshold {id="find-threshold",version="3.5",tag="command"}
|
||||
|
||||
Runs prediction trials for a trained model with varying tresholds to maximize
|
||||
Runs prediction trials for a trained model with varying thresholds to maximize
|
||||
the specified metric. The search space for the threshold is traversed linearly
|
||||
from 0 to 1 in `n_trials` steps. Results are displayed in a table on `stdout`
|
||||
(the corresponding API call to `spacy.cli.find_threshold.find_threshold()`
|
||||
|
|
|
|||
|
|
@ -67,7 +67,7 @@ architectures and their arguments and hyperparameters.
|
|||
| `generate_empty_kb` <Tag variant="new">3.5.1</Tag> | Function that generates an empty `KnowledgeBase` object. Defaults to [`spacy.EmptyKB.v2`](/api/architectures#EmptyKB), which generates an empty [`InMemoryLookupKB`](/api/inmemorylookupkb). ~~Callable[[Vocab, int], KnowledgeBase]~~ |
|
||||
| `overwrite` <Tag variant="new">3.2</Tag> | Whether existing annotation is overwritten. Defaults to `True`. ~~bool~~ |
|
||||
| `scorer` <Tag variant="new">3.2</Tag> | The scoring method. Defaults to [`Scorer.score_links`](/api/scorer#score_links). ~~Optional[Callable]~~ |
|
||||
| `threshold` <Tag variant="new">3.4</Tag> | Confidence threshold for entity predictions. The default of `None` implies that all predictions are accepted, otherwise those with a score beneath the treshold are discarded. If there are no predictions with scores above the threshold, the linked entity is `NIL`. ~~Optional[float]~~ |
|
||||
| `threshold` <Tag variant="new">3.4</Tag> | Confidence threshold for entity predictions. The default of `None` implies that all predictions are accepted, otherwise those with a score beneath the threshold are discarded. If there are no predictions with scores above the threshold, the linked entity is `NIL`. ~~Optional[float]~~ |
|
||||
|
||||
```python
|
||||
%%GITHUB_SPACY/spacy/pipeline/entity_linker.py
|
||||
|
|
@ -100,21 +100,21 @@ custom knowledge base, you should either call
|
|||
[`set_kb`](/api/entitylinker#set_kb) or provide a `kb_loader` in the
|
||||
[`initialize`](/api/entitylinker#initialize) call.
|
||||
|
||||
| Name | Description |
|
||||
| ---------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| `vocab` | The shared vocabulary. ~~Vocab~~ |
|
||||
| `model` | The [`Model`](https://thinc.ai/docs/api-model) powering the pipeline component. ~~Model~~ |
|
||||
| `name` | String name of the component instance. Used to add entries to the `losses` during training. ~~str~~ |
|
||||
| _keyword-only_ | |
|
||||
| `entity_vector_length` | Size of encoding vectors in the KB. ~~int~~ |
|
||||
| `get_candidates` | Function that generates plausible candidates for a given `Span` object. ~~Callable[[KnowledgeBase, Span], Iterable[Candidate]]~~ |
|
||||
| `labels_discard` | NER labels that will automatically get a `"NIL"` prediction. ~~Iterable[str]~~ |
|
||||
| `n_sents` | The number of neighbouring sentences to take into account. ~~int~~ |
|
||||
| `incl_prior` | Whether or not to include prior probabilities from the KB in the model. ~~bool~~ |
|
||||
| `incl_context` | Whether or not to include the local context in the model. ~~bool~~ |
|
||||
| `overwrite` <Tag variant="new">3.2</Tag> | Whether existing annotation is overwritten. Defaults to `True`. ~~bool~~ |
|
||||
| `scorer` <Tag variant="new">3.2</Tag> | The scoring method. Defaults to [`Scorer.score_links`](/api/scorer#score_links). ~~Optional[Callable]~~ |
|
||||
| `threshold` <Tag variant="new">3.4</Tag> | Confidence threshold for entity predictions. The default of `None` implies that all predictions are accepted, otherwise those with a score beneath the treshold are discarded. If there are no predictions with scores above the threshold, the linked entity is `NIL`. ~~Optional[float]~~ |
|
||||
| Name | Description |
|
||||
| ---------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| `vocab` | The shared vocabulary. ~~Vocab~~ |
|
||||
| `model` | The [`Model`](https://thinc.ai/docs/api-model) powering the pipeline component. ~~Model~~ |
|
||||
| `name` | String name of the component instance. Used to add entries to the `losses` during training. ~~str~~ |
|
||||
| _keyword-only_ | |
|
||||
| `entity_vector_length` | Size of encoding vectors in the KB. ~~int~~ |
|
||||
| `get_candidates` | Function that generates plausible candidates for a given `Span` object. ~~Callable[[KnowledgeBase, Span], Iterable[Candidate]]~~ |
|
||||
| `labels_discard` | NER labels that will automatically get a `"NIL"` prediction. ~~Iterable[str]~~ |
|
||||
| `n_sents` | The number of neighbouring sentences to take into account. ~~int~~ |
|
||||
| `incl_prior` | Whether or not to include prior probabilities from the KB in the model. ~~bool~~ |
|
||||
| `incl_context` | Whether or not to include the local context in the model. ~~bool~~ |
|
||||
| `overwrite` <Tag variant="new">3.2</Tag> | Whether existing annotation is overwritten. Defaults to `True`. ~~bool~~ |
|
||||
| `scorer` <Tag variant="new">3.2</Tag> | The scoring method. Defaults to [`Scorer.score_links`](/api/scorer#score_links). ~~Optional[Callable]~~ |
|
||||
| `threshold` <Tag variant="new">3.4</Tag> | Confidence threshold for entity predictions. The default of `None` implies that all predictions are accepted, otherwise those with a score beneath the threshold are discarded. If there are no predictions with scores above the threshold, the linked entity is `NIL`. ~~Optional[float]~~ |
|
||||
|
||||
## EntityLinker.\_\_call\_\_ {id="call",tag="method"}
|
||||
|
||||
|
|
|
|||
|
|
@ -58,7 +58,7 @@ how the component should be configured. You can override its settings via the
|
|||
| Setting | Description |
|
||||
| ---------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| `phrase_matcher_attr` | Optional attribute name match on for the internal [`PhraseMatcher`](/api/phrasematcher), e.g. `LOWER` to match on the lowercase token text. Defaults to `None`. ~~Optional[Union[int, str]]~~ |
|
||||
| `matcher_fuzzy_compare` <Tag variant="new">3.5</Tag> | The fuzzy comparison method, passed on to the internal `Matcher`. Defaults to `spacy.matcher.levenshtein.levenshtein_compare`. ~~Callable~~ |
|
||||
| `matcher_fuzzy_compare` <Tag variant="new">3.5</Tag> | The fuzzy comparison method, passed on to the internal `Matcher`. Defaults to `spacy.matcher.levenshtein.levenshtein_compare`. ~~Callable~~ |
|
||||
| `validate` | Whether patterns should be validated (passed to the `Matcher` and `PhraseMatcher`). Defaults to `False`. ~~bool~~ |
|
||||
| `overwrite_ents` | If existing entities are present, e.g. entities added by the model, overwrite them by matches if necessary. Defaults to `False`. ~~bool~~ |
|
||||
| `ent_id_sep` | Separator used internally for entity IDs. Defaults to `"\|\|"`. ~~str~~ |
|
||||
|
|
@ -92,7 +92,7 @@ be a token pattern (list) or a phrase pattern (string). For example:
|
|||
| `name` <Tag variant="new">3</Tag> | Instance name of the current pipeline component. Typically passed in automatically from the factory when the component is added. Used to disable the current entity ruler while creating phrase patterns with the nlp object. ~~str~~ |
|
||||
| _keyword-only_ | |
|
||||
| `phrase_matcher_attr` | Optional attribute name match on for the internal [`PhraseMatcher`](/api/phrasematcher), e.g. `LOWER` to match on the lowercase token text. Defaults to `None`. ~~Optional[Union[int, str]]~~ |
|
||||
| `matcher_fuzzy_compare` <Tag variant="new">3.5</Tag> | The fuzzy comparison method, passed on to the internal `Matcher`. Defaults to `spacy.matcher.levenshtein.levenshtein_compare`. ~~Callable~~ |
|
||||
| `matcher_fuzzy_compare` <Tag variant="new">3.5</Tag> | The fuzzy comparison method, passed on to the internal `Matcher`. Defaults to `spacy.matcher.levenshtein.levenshtein_compare`. ~~Callable~~ |
|
||||
| `validate` | Whether patterns should be validated, passed to Matcher and PhraseMatcher as `validate`. Defaults to `False`. ~~bool~~ |
|
||||
| `overwrite_ents` | If existing entities are present, e.g. entities added by the model, overwrite them by matches if necessary. Defaults to `False`. ~~bool~~ |
|
||||
| `ent_id_sep` | Separator used internally for entity IDs. Defaults to `"\|\|"`. ~~str~~ |
|
||||
|
|
@ -173,7 +173,7 @@ happens automatically after the component has been added to the pipeline using
|
|||
[`nlp.add_pipe`](/api/language#add_pipe). If the entity ruler was initialized
|
||||
with `overwrite_ents=True`, existing entities will be replaced if they overlap
|
||||
with the matches. When matches overlap in a Doc, the entity ruler prioritizes
|
||||
longer patterns over shorter, and if equal the match occuring first in the Doc
|
||||
longer patterns over shorter, and if equal the match occurring first in the Doc
|
||||
is chosen.
|
||||
|
||||
> #### Example
|
||||
|
|
|
|||
|
|
@ -288,7 +288,7 @@ it – so no NP-level coordination, no prepositional phrases, and no relative
|
|||
clauses.
|
||||
|
||||
If the `noun_chunk` [syntax iterator](/usage/linguistic-features#language-data)
|
||||
has not been implemeted for the given language, a `NotImplementedError` is
|
||||
has not been implemented for the given language, a `NotImplementedError` is
|
||||
raised.
|
||||
|
||||
> #### Example
|
||||
|
|
|
|||
|
|
@ -416,7 +416,7 @@ by this class. Instances of this class are typically assigned to the
|
|||
| `align` | Alignment from the `Doc`'s tokenization to the wordpieces. This is a ragged array, where `align.lengths[i]` indicates the number of wordpiece tokens that token `i` aligns against. The actual indices are provided at `align[i].dataXd`. ~~Ragged~~ |
|
||||
| `width` | The width of the last hidden layer. ~~int~~ |
|
||||
|
||||
### TransformerData.empty {id="transformerdata-emoty",tag="classmethod"}
|
||||
### TransformerData.empty {id="transformerdata-empty",tag="classmethod"}
|
||||
|
||||
Create an empty `TransformerData` container.
|
||||
|
||||
|
|
|
|||
|
|
@ -832,7 +832,7 @@ retrieve and add to them.
|
|||
|
||||
After creation, the component needs to be
|
||||
[initialized](/usage/training#initialization). This method can define the
|
||||
relevant labels in two ways: explicitely by setting the `labels` argument in the
|
||||
relevant labels in two ways: explicitly by setting the `labels` argument in the
|
||||
[`initialize` block](/api/data-formats#config-initialize) of the config, or
|
||||
implicately by deducing them from the `get_examples` callback that generates the
|
||||
full **training data set**, or a representative sample.
|
||||
|
|
|
|||
|
|
@ -1899,7 +1899,7 @@ the two words.
|
|||
"Shore": ("coast", 0.732257),
|
||||
"Precautionary": ("caution", 0.490973),
|
||||
"hopelessness": ("sadness", 0.742366),
|
||||
"Continous": ("continuous", 0.732549),
|
||||
"Continuous": ("continuous", 0.732549),
|
||||
"Disemboweled": ("corpse", 0.499432),
|
||||
"biostatistician": ("scientist", 0.339724),
|
||||
"somewheres": ("somewheres", 0.402736),
|
||||
|
|
|
|||
|
|
@ -173,7 +173,7 @@ detected, a corresponding warning is displayed. If you'd like to disable the
|
|||
dependency check, set `check_requirements: false` in your project's
|
||||
`project.yml`.
|
||||
|
||||
### 4. Run a workflow {id="run-workfow"}
|
||||
### 4. Run a workflow {id="run-workflow"}
|
||||
|
||||
> #### project.yml
|
||||
>
|
||||
|
|
@ -286,7 +286,7 @@ pipelines.
|
|||
| --------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
|
||||
| `title` | An optional project title used in `--help` message and [auto-generated docs](#custom-docs). |
|
||||
| `description` | An optional project description used in [auto-generated docs](#custom-docs). |
|
||||
| `vars` | A dictionary of variables that can be referenced in paths, URLs and scripts and overriden on the CLI, just like [`config.cfg` variables](/usage/training#config-interpolation). For example, `${vars.name}` will use the value of the variable `name`. Variables need to be defined in the section `vars`, but can be a nested dict, so you're able to reference `${vars.model.name}`. |
|
||||
| `vars` | A dictionary of variables that can be referenced in paths, URLs and scripts and overridden on the CLI, just like [`config.cfg` variables](/usage/training#config-interpolation). For example, `${vars.name}` will use the value of the variable `name`. Variables need to be defined in the section `vars`, but can be a nested dict, so you're able to reference `${vars.model.name}`. |
|
||||
| `env` | A dictionary of variables, mapped to the names of environment variables that will be read in when running the project. For example, `${env.name}` will use the value of the environment variable defined as `name`. |
|
||||
| `directories` | An optional list of [directories](#project-files) that should be created in the project for assets, training outputs, metrics etc. spaCy will make sure that these directories always exist. |
|
||||
| `assets` | A list of assets that can be fetched with the [`project assets`](/api/cli#project-assets) command. `url` defines a URL or local path, `dest` is the destination file relative to the project directory, and an optional `checksum` ensures that an error is raised if the file's checksum doesn't match. Instead of `url`, you can also provide a `git` block with the keys `repo`, `branch` and `path`, to download from a Git repo. |
|
||||
|
|
|
|||
|
|
@ -306,7 +306,9 @@ installed in the same environment – that's it.
|
|||
|
||||
### Loading probability tables into existing models
|
||||
|
||||
You can load a probability table from [spacy-lookups-data](https://github.com/explosion/spacy-lookups-data) into an existing spaCy model like `en_core_web_sm`.
|
||||
You can load a probability table from
|
||||
[spacy-lookups-data](https://github.com/explosion/spacy-lookups-data) into an
|
||||
existing spaCy model like `en_core_web_sm`.
|
||||
|
||||
```python
|
||||
# Requirements: pip install spacy-lookups-data
|
||||
|
|
@ -317,7 +319,8 @@ lookups = load_lookups("en", ["lexeme_prob"])
|
|||
nlp.vocab.lookups.add_table("lexeme_prob", lookups.get_table("lexeme_prob"))
|
||||
```
|
||||
|
||||
When training a model from scratch you can also specify probability tables in the `config.cfg`.
|
||||
When training a model from scratch you can also specify probability tables in
|
||||
the `config.cfg`.
|
||||
|
||||
```ini {title="config.cfg (excerpt)"}
|
||||
[initialize.lookups]
|
||||
|
|
@ -346,8 +349,8 @@ them**!
|
|||
To stick with the theme of
|
||||
[this entry points blog post](https://amir.rachum.com/blog/2017/07/28/python-entry-points/),
|
||||
consider the following custom spaCy
|
||||
[pipeline component](/usage/processing-pipelines#custom-coponents) that prints a
|
||||
snake when it's called:
|
||||
[pipeline component](/usage/processing-pipelines#custom-components) that prints
|
||||
a snake when it's called:
|
||||
|
||||
> #### Package directory structure
|
||||
>
|
||||
|
|
|
|||
|
|
@ -185,7 +185,7 @@ New: 'ORG' (23860), 'PERSON' (21395), 'GPE' (21193), 'DATE' (18080), 'CARDINAL'
|
|||
'LOC' (2113), 'TIME' (1616), 'WORK_OF_ART' (1229), 'QUANTITY' (1150), 'FAC'
|
||||
(1134), 'EVENT' (974), 'PRODUCT' (935), 'LAW' (444), 'LANGUAGE' (338)
|
||||
✔ Good amount of examples for all labels
|
||||
✔ Examples without occurences available for all labels
|
||||
✔ Examples without occurrences available for all labels
|
||||
✔ No entities consisting of or starting/ending with whitespace
|
||||
|
||||
=========================== Part-of-speech Tagging ===========================
|
||||
|
|
|
|||
|
|
@ -138,7 +138,7 @@ backwards compatibility, the tuple format remains available under
|
|||
`TransformerData.tensors` and `FullTransformerBatch.tensors`. See more details
|
||||
in the [transformer API docs](/api/architectures#TransformerModel).
|
||||
|
||||
`spacy-transfomers` v1.1 also adds support for `transformer_config` settings
|
||||
`spacy-transformers` v1.1 also adds support for `transformer_config` settings
|
||||
such as `output_attentions`. Additional output is stored under
|
||||
`TransformerData.model_output`. More details are in the
|
||||
[TransformerModel docs](/api/architectures#TransformerModel). The training speed
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user