repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
value | license stringclasses 7
values | commit_sha stringlengths 40 40 | retrieved_at stringdate 2026-01-04 14:38:15 2026-01-05 02:33:18 | truncated bool 2
classes |
|---|---|---|---|---|---|---|---|---|
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/scorer.py | spacy/scorer.py | from collections import defaultdict
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
Iterable,
List,
Optional,
Set,
Tuple,
)
import numpy as np
from .errors import Errors
from .morphology import Morphology
from .tokens import Doc, Span, Token
from .training import Example
f... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | true |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/__main__.py | spacy/__main__.py | if __name__ == "__main__":
from spacy.cli import setup_cli
setup_cli()
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/pipe_analysis.py | spacy/pipe_analysis.py | from typing import TYPE_CHECKING, Dict, ItemsView, Iterable, List, Set, Union
from wasabi import msg
from .errors import Errors
from .tokens import Doc, Span, Token
from .util import dot_to_dict
if TYPE_CHECKING:
# This lets us add type hints for mypy etc. without causing circular imports
from .language impo... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ty.py | spacy/ty.py | from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
Iterable,
List,
Optional,
Sequence,
)
from thinc.api import Model, Optimizer
from .compat import Protocol, runtime_checkable
if TYPE_CHECKING:
from .language import Language
from .training import Example
@runtime_check... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/errors.py | spacy/errors.py | import warnings
from .compat import Literal
class ErrorsWithCodes(type):
def __getattribute__(self, code):
msg = super().__getattribute__(code)
if code.startswith("__"): # python system attributes like __class__
return msg
else:
return "[{code}] {msg}".format(code... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | true |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/__init__.py | spacy/__init__.py | import sys
from pathlib import Path
from typing import Any, Dict, Iterable, Union
# set library-specific custom warning handling before doing anything else
from .errors import setup_default_warnings
setup_default_warnings() # noqa: E402
# These are imported as part of the API
from thinc.api import Config, prefer_gp... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/about.py | spacy/about.py | # fmt: off
__title__ = "spacy"
__version__ = "3.8.11"
__download_url__ = "https://github.com/explosion/spacy-models/releases/download"
__compatibility__ = "https://raw.githubusercontent.com/explosion/spacy-models/master/compatibility.json"
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/matcher/__init__.py | spacy/matcher/__init__.py | from .dependencymatcher import DependencyMatcher
from .levenshtein import levenshtein
from .matcher import Matcher
from .phrasematcher import PhraseMatcher
__all__ = ["DependencyMatcher", "Matcher", "PhraseMatcher", "levenshtein"]
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ml/featureextractor.py | spacy/ml/featureextractor.py | from typing import Callable, List, Tuple, Union
from thinc.api import Model, registry
from thinc.types import Ints2d
from ..tokens import Doc
def FeatureExtractor(
columns: Union[List[str], List[int], List[Union[int, str]]],
) -> Model[List[Doc], List[Ints2d]]:
return Model("extract_features", forward, attr... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ml/staticvectors.py | spacy/ml/staticvectors.py | import warnings
from typing import Callable, List, Optional, Sequence, Tuple, cast
from thinc.api import Model, Ops, registry
from thinc.initializers import glorot_uniform_init
from thinc.types import Floats1d, Floats2d, Ints1d, Ragged
from thinc.util import partial
from ..attrs import ORTH
from ..errors import Error... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ml/callbacks.py | spacy/ml/callbacks.py | import functools
import inspect
import types
import warnings
from typing import TYPE_CHECKING, Callable, Dict, List, Optional, Set, Type
from thinc.layers import with_nvtx_range
from thinc.model import Model, wrap_model_recursive
from thinc.util import use_nvtx_range
from ..errors import Warnings
from ..util import r... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ml/extract_spans.py | spacy/ml/extract_spans.py | from typing import Callable, List, Tuple
from thinc.api import Model, to_numpy
from thinc.types import Ints1d, Ragged
from ..util import registry
def extract_spans() -> Model[Tuple[Ragged, Ragged], Ragged]:
"""Extract spans from a sequence of source arrays, as specified by an array
of (start, end) indices. ... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ml/tb_framework.py | spacy/ml/tb_framework.py | from thinc.api import Model, noop
from ..util import registry
from .parser_model import ParserStepModel
def TransitionModel(
tok2vec, lower, upper, resize_output, dropout=0.2, unseen_classes=set()
):
"""Set up a stepwise transition-based model"""
if upper is None:
has_upper = False
upper ... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ml/_character_embed.py | spacy/ml/_character_embed.py | from typing import List
from thinc.api import Model
from thinc.types import Floats2d
from ..tokens import Doc
from ..util import registry
def CharacterEmbed(nM: int, nC: int) -> Model[List[Doc], List[Floats2d]]:
# nM: Number of dimensions per character. nC: Number of characters.
return Model(
"chare... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ml/_precomputable_affine.py | spacy/ml/_precomputable_affine.py | from thinc.api import Model, normal_init
from ..util import registry
def PrecomputableAffine(nO, nI, nF, nP, dropout=0.1):
model = Model(
"precomputable_affine",
forward,
init=init,
dims={"nO": nO, "nI": nI, "nF": nF, "nP": nP},
params={"W": None, "b": None, "pad": None},
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ml/__init__.py | spacy/ml/__init__.py | from .callbacks import create_models_with_nvtx_range # noqa: F401
from .models import * # noqa: F401, F403
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ml/extract_ngrams.py | spacy/ml/extract_ngrams.py | from thinc.api import Model
from ..attrs import LOWER
from ..util import registry
def extract_ngrams(ngram_size: int, attr: int = LOWER) -> Model:
model: Model = Model("extract_ngrams", forward)
model.attrs["ngram_size"] = ngram_size
model.attrs["attr"] = attr
return model
def forward(model: Model,... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ml/models/multi_task.py | spacy/ml/models/multi_task.py | from functools import partial
from typing import TYPE_CHECKING, Any, Callable, Iterable, List, Optional, Tuple, cast
import numpy
from thinc.api import (
CosineDistance,
L2Distance,
LayerNorm,
Linear,
Maxout,
Model,
MultiSoftmax,
Softmax,
chain,
list2array,
to_categorical,
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ml/models/textcat.py | spacy/ml/models/textcat.py | from functools import partial
from typing import List, Optional, Tuple, cast
from thinc.api import (
Dropout,
Gelu,
LayerNorm,
Linear,
Logistic,
Maxout,
Model,
ParametricAttention,
ParametricAttention_v2,
Relu,
Softmax,
SparseLinear,
SparseLinear_v2,
chain,
c... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ml/models/tok2vec.py | spacy/ml/models/tok2vec.py | from typing import List, Optional, Union, cast
from thinc.api import (
HashEmbed,
Maxout,
Mish,
Model,
PyTorchLSTM,
chain,
clone,
concatenate,
expand_window,
list2ragged,
noop,
ragged2list,
residual,
with_array,
with_padded,
)
from thinc.types import Floats2d... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ml/models/entity_linker.py | spacy/ml/models/entity_linker.py | from pathlib import Path
from typing import Callable, Iterable, List, Optional, Tuple
from thinc.api import (
Linear,
Maxout,
Model,
Ragged,
chain,
list2ragged,
reduce_mean,
residual,
tuplify,
)
from thinc.types import Floats2d
from ...errors import Errors
from ...kb import (
C... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ml/models/parser.py | spacy/ml/models/parser.py | from typing import List, Optional, cast
from thinc.api import Linear, Model, chain, list2array, use_ops, zero_init
from thinc.types import Floats2d
from ...compat import Literal
from ...errors import Errors
from ...tokens import Doc
from ...util import registry
from .._precomputable_affine import PrecomputableAffine
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ml/models/tagger.py | spacy/ml/models/tagger.py | from typing import List, Optional
from thinc.api import Model, Softmax_v2, chain, with_array, zero_init
from thinc.types import Floats2d
from ...tokens import Doc
from ...util import registry
def build_tagger_model(
tok2vec: Model[List[Doc], List[Floats2d]], nO: Optional[int] = None, normalize=False
) -> Model[... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ml/models/span_finder.py | spacy/ml/models/span_finder.py | from typing import Callable, List, Tuple
from thinc.api import Model, chain, with_array
from thinc.types import Floats1d, Floats2d
from ...tokens import Doc
from ...util import registry
InT = List[Doc]
OutT = Floats2d
def build_finder_model(
tok2vec: Model[InT, List[Floats2d]], scorer: Model[OutT, OutT]
) -> M... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ml/models/__init__.py | spacy/ml/models/__init__.py | from .entity_linker import * # noqa
from .multi_task import * # noqa
from .parser import * # noqa
from .span_finder import * # noqa
from .spancat import * # noqa
from .tagger import * # noqa
from .textcat import * # noqa
from .tok2vec import * # noqa
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/ml/models/spancat.py | spacy/ml/models/spancat.py | from typing import List, Tuple, cast
from thinc.api import (
Linear,
Logistic,
Maxout,
Model,
chain,
concatenate,
glorot_uniform_init,
list2ragged,
reduce_first,
reduce_last,
reduce_max,
reduce_mean,
with_getitem,
)
from thinc.types import Floats2d, Ragged
from ...t... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/char_classes.py | spacy/lang/char_classes.py | split_chars = lambda char: list(char.strip().split(" "))
merge_chars = lambda char: char.strip().replace(" ", "|")
group_chars = lambda char: char.strip().replace(" ", "")
_ethiopic = r"\u1200-\u137F"
_bengali = r"\u0980-\u09FF"
_hebrew = r"\u0591-\u05F4\uFB1D-\uFB4F"
_hindi = r"\u0900-\u097F"
_kannada = r"\u0C80-... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/tokenizer_exceptions.py | spacy/lang/tokenizer_exceptions.py | import re
from ..symbols import NORM, ORTH
from .char_classes import ALPHA_LOWER
# URL validation regex courtesy of: https://mathiasbynens.be/demo/url-regex
# and https://gist.github.com/dperini/729294 (Diego Perini, MIT License)
# A few mods to this regex to account for use cases represented in test_urls
URL_PATTERN... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/__init__.py | spacy/lang/__init__.py | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false | |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/punctuation.py | spacy/lang/punctuation.py | from .char_classes import (
ALPHA,
ALPHA_LOWER,
ALPHA_UPPER,
COMBINING_DIACRITICS,
CONCAT_QUOTES,
CURRENCY,
HYPHENS,
LIST_CURRENCY,
LIST_ELLIPSES,
LIST_ICONS,
LIST_PUNCT,
LIST_QUOTES,
PUNCT,
UNITS,
)
TOKENIZER_PREFIXES = (
["§", "%", "=", "—", "–", r"\+(?![0-... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/lex_attrs.py | spacy/lang/lex_attrs.py | import re
import unicodedata
from typing import Set
from .. import attrs
from .tokenizer_exceptions import URL_MATCH
_like_email = re.compile(r"([a-zA-Z0-9_.+-]+@[a-zA-Z0-9-]+\.[a-zA-Z0-9-.]+)").match
_tlds = set(
"com|org|edu|gov|net|mil|aero|asia|biz|cat|coop|info|int|jobs|mobi|museum|"
"name|pro|tel|travel... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/norm_exceptions.py | spacy/lang/norm_exceptions.py | # These exceptions are used to add NORM values based on a token's ORTH value.
# Individual languages can also add their own exceptions and overwrite them -
# for example, British vs. American spelling in English.
# Norms are only set if no alternative is provided in the tokenizer exceptions.
# Note that this does not ... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/kn/__init__.py | spacy/lang/kn/__init__.py | from ...language import BaseDefaults, Language
from .stop_words import STOP_WORDS
class KannadaDefaults(BaseDefaults):
stop_words = STOP_WORDS
class Kannada(Language):
lang = "kn"
Defaults = KannadaDefaults
__all__ = ["Kannada"]
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/kn/examples.py | spacy/lang/kn/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.en.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"ಆಪಲ್ ಒಂದು ಯು.ಕೆ. ಸ್ಟಾರ್ಟ್ಅಪ್ ಅನ್ನು ೧ ಶತಕೋಟಿ ಡಾಲರ್ಗಳಿಗೆ ಖರೀದಿಸಲು ನೋಡುತ್ತಿದೆ.",
"ಸ್ವಾಯತ್ತ ಕಾರುಗಳು ವಿಮಾ ಹೊಣೆಗಾರಿಕೆಯನ್ನು ತಯಾರಕರ ಕಡೆಗೆ ಬದಲಾಯಿಸುತ್ತವೆ.",
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/kn/stop_words.py | spacy/lang/kn/stop_words.py | STOP_WORDS = set(
"""
ಹಲವು
ಮೂಲಕ
ಹಾಗೂ
ಅದು
ನೀಡಿದ್ದಾರೆ
ಯಾವ
ಎಂದರು
ಅವರು
ಈಗ
ಎಂಬ
ಹಾಗಾಗಿ
ಅಷ್ಟೇ
ನಾವು
ಇದೇ
ಹೇಳಿ
ತಮ್ಮ
ಹೀಗೆ
ನಮ್ಮ
ಬೇರೆ
ನೀಡಿದರು
ಮತ್ತೆ
ಇದು
ಈ
ನೀವು
ನಾನು
ಇತ್ತು
ಎಲ್ಲಾ
ಯಾವುದೇ
ನಡೆದ
ಅದನ್ನು
ಎಂದರೆ
ನೀಡಿದೆ
ಹೀಗಾಗಿ
ಜೊತೆಗೆ
ಇದರಿಂದ
ನನಗೆ
ಅಲ್ಲದೆ
ಎಷ್ಟು
ಇದರ
ಇಲ್ಲ
ಕಳೆದ
ತುಂಬಾ
ಈಗಾಗಲೇ
ಮಾಡಿ
ಅದಕ್ಕೆ
ಬಗ್ಗೆ
ಅವರ
ಇದನ್ನು
ಆ
ಇದೆ
ಹೆಚ್ಚು
ಇನ್ನು
ಎಲ್ಲ
ಇ... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ml/__init__.py | spacy/lang/ml/__init__.py | from ...language import BaseDefaults, Language
from .lex_attrs import LEX_ATTRS
from .stop_words import STOP_WORDS
class MalayalamDefaults(BaseDefaults):
lex_attr_getters = LEX_ATTRS
stop_words = STOP_WORDS
class Malayalam(Language):
lang = "ml"
Defaults = MalayalamDefaults
__all__ = ["Malayalam"]... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ml/examples.py | spacy/lang/ml/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.ml.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"അനാവശ്യമായി കണ്ണിലും മൂക്കിലും വായിലും സ്പർശിക്കാതിരിക്കുക",
"പൊതുരംഗത്ത് മലയാള ഭാഷയുടെ സമഗ്രപുരോഗതി ലക്ഷ്യമാക്കി പ്രവർത്തിക്കുന്ന സംഘടനയായ മലയാളഐക്യവ... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ml/lex_attrs.py | spacy/lang/ml/lex_attrs.py | from ...attrs import LIKE_NUM
# reference 2: https://www.omniglot.com/language/numbers/malayalam.htm
_num_words = [
"പൂജ്യം ",
"ഒന്ന് ",
"രണ്ട് ",
"മൂന്ന് ",
"നാല് ",
"അഞ്ച് ",
"ആറ് ",
"ഏഴ് ",
"എട്ട് ",
"ഒന്പത് ",
"പത്ത് ",
"പതിനൊന്ന്",
"പന്ത്രണ്ട്",
"പതി മൂന്... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ml/stop_words.py | spacy/lang/ml/stop_words.py | STOP_WORDS = set(
"""
അത്
ഇത്
ആയിരുന്നു
ആകുന്നു
വരെ
അന്നേരം
അന്ന്
ഇന്ന്
ആണ്
""".split()
)
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ur/__init__.py | spacy/lang/ur/__init__.py | from ...language import BaseDefaults, Language
from .lex_attrs import LEX_ATTRS
from .punctuation import TOKENIZER_SUFFIXES
from .stop_words import STOP_WORDS
class UrduDefaults(BaseDefaults):
suffixes = TOKENIZER_SUFFIXES
lex_attr_getters = LEX_ATTRS
stop_words = STOP_WORDS
writing_system = {"directi... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ur/punctuation.py | spacy/lang/ur/punctuation.py | from ..punctuation import TOKENIZER_SUFFIXES
_suffixes = TOKENIZER_SUFFIXES
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ur/examples.py | spacy/lang/ur/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.da.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"اردو ہے جس کا نام ہم جانتے ہیں داغ",
"سارے جہاں میں دھوم ہماری زباں کی ہے",
]
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ur/lex_attrs.py | spacy/lang/ur/lex_attrs.py | from ...attrs import LIKE_NUM
# Source https://quizlet.com/4271889/1-100-urdu-number-wordsurdu-numerals-flash-cards/
# http://www.urduword.com/lessons.php?lesson=numbers
# https://en.wikibooks.org/wiki/Urdu/Vocabulary/Numbers
# https://www.urdu-english.com/lessons/beginner/numbers
_num_words = """ایک دو تین چار پانچ ... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ur/stop_words.py | spacy/lang/ur/stop_words.py | # Source: collected from different resource on internet
STOP_WORDS = set(
"""
ثھی
خو
گی
اپٌے
گئے
ثہت
طرف
ہوبری
پبئے
اپٌب
دوضری
گیب
کت
گب
ثھی
ضے
ہر
پر
اش
دی
گے
لگیں
ہے
ثعذ
ضکتے
تھی
اى
دیب
لئے
والے
یہ
ثدبئے
ضکتی
تھب
اًذر
رریعے
لگی
ہوبرا
ہوًے
ثبہر
ضکتب
ًہیں
تو
اور
رہب
لگے
ہوضکتب
ہوں
کب
ہوبرے
توبم
کیب
ایطے
رہی
هگر
ہوضک... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/de/tokenizer_exceptions.py | spacy/lang/de/tokenizer_exceptions.py | from ...symbols import NORM, ORTH
from ...util import update_exc
from ..tokenizer_exceptions import BASE_EXCEPTIONS
_exc = {
"auf'm": [{ORTH: "auf"}, {ORTH: "'m", NORM: "dem"}],
"du's": [{ORTH: "du"}, {ORTH: "'s", NORM: "es"}],
"er's": [{ORTH: "er"}, {ORTH: "'s", NORM: "es"}],
"hinter'm": [{ORTH: "hint... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/de/__init__.py | spacy/lang/de/__init__.py | from ...language import BaseDefaults, Language
from .punctuation import TOKENIZER_INFIXES, TOKENIZER_PREFIXES, TOKENIZER_SUFFIXES
from .stop_words import STOP_WORDS
from .syntax_iterators import SYNTAX_ITERATORS
from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
class GermanDefaults(BaseDefaults):
tokenizer_e... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/de/punctuation.py | spacy/lang/de/punctuation.py | from ..char_classes import (
ALPHA,
ALPHA_LOWER,
ALPHA_UPPER,
CONCAT_QUOTES,
CURRENCY,
LIST_ELLIPSES,
LIST_ICONS,
LIST_PUNCT,
LIST_QUOTES,
PUNCT,
UNITS,
)
from ..punctuation import TOKENIZER_PREFIXES as BASE_TOKENIZER_PREFIXES
_prefixes = ["``"] + BASE_TOKENIZER_PREFIXES
_s... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/de/syntax_iterators.py | spacy/lang/de/syntax_iterators.py | from typing import Iterator, Tuple, Union
from ...errors import Errors
from ...symbols import NOUN, PRON, PROPN
from ...tokens import Doc, Span
def noun_chunks(doclike: Union[Doc, Span]) -> Iterator[Tuple[int, int, int]]:
"""Detect base noun phrases from a dependency parse. Works on Doc and Span."""
# this i... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/de/examples.py | spacy/lang/de/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.de.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"Die ganze Stadt ist ein Startup: Shenzhen ist das Silicon Valley für Hardware-Firmen",
"Wie deutsche Startups die Technologie vorantreiben wollen: Kün... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/de/stop_words.py | spacy/lang/de/stop_words.py | STOP_WORDS = set(
"""
á a ab aber ach acht achte achten achter achtes ag alle allein allem allen
aller allerdings alles allgemeinen als also am an andere anderen anderem andern
anders auch auf aus ausser außer ausserdem außerdem
bald bei beide beiden beim beispiel bekannt bereits besonders besser besten bin
bis bi... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/sk/__init__.py | spacy/lang/sk/__init__.py | from ...language import BaseDefaults, Language
from .lex_attrs import LEX_ATTRS
from .stop_words import STOP_WORDS
class SlovakDefaults(BaseDefaults):
lex_attr_getters = LEX_ATTRS
stop_words = STOP_WORDS
class Slovak(Language):
lang = "sk"
Defaults = SlovakDefaults
__all__ = ["Slovak"]
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/sk/examples.py | spacy/lang/sk/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.sk.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"Ardevop, s.r.o. je malá startup firma na území SR.",
"Samojazdiace autá presúvajú poistnú zodpovednosť na výrobcov automobilov.",
"Košice sú na vý... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/sk/lex_attrs.py | spacy/lang/sk/lex_attrs.py | from ...attrs import LIKE_NUM
_num_words = [
"nula",
"jeden",
"dva",
"tri",
"štyri",
"päť",
"šesť",
"sedem",
"osem",
"deväť",
"desať",
"jedenásť",
"dvanásť",
"trinásť",
"štrnásť",
"pätnásť",
"šestnásť",
"sedemnásť",
"osemnásť",
"devätnásť"... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/sk/stop_words.py | spacy/lang/sk/stop_words.py | # Source: https://github.com/Ardevop-sk/stopwords-sk
STOP_WORDS = set(
"""
a
aby
aj
ak
akej
akejže
ako
akom
akomže
akou
akouže
akože
aká
akáže
aké
akého
akéhože
akému
akémuže
akéže
akú
akúže
aký
akých
akýchže
akým
akými
akýmiže
akýmže
akýže
ale
alebo
ani
asi
avšak
až
ba
bez
bezo
bol
bola
boli
bolo
bude
budem
budem... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/az/__init__.py | spacy/lang/az/__init__.py | from ...language import BaseDefaults, Language
from .lex_attrs import LEX_ATTRS
from .stop_words import STOP_WORDS
class AzerbaijaniDefaults(BaseDefaults):
lex_attr_getters = LEX_ATTRS
stop_words = STOP_WORDS
class Azerbaijani(Language):
lang = "az"
Defaults = AzerbaijaniDefaults
__all__ = ["Azerb... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/az/examples.py | spacy/lang/az/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.az.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"Bu bir cümlədir.",
"Necəsən?",
"Qarabağ ordeni vətən müharibəsində qələbə münasibəti ilə təsis edilmişdir.",
"Məktəbimizə Bakıdan bir tarix müə... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/az/lex_attrs.py | spacy/lang/az/lex_attrs.py | from ...attrs import LIKE_NUM
# Eleven, twelve etc. are written separate: on bir, on iki
_num_words = [
"bir",
"iki",
"üç",
"dörd",
"beş",
"altı",
"yeddi",
"səkkiz",
"doqquz",
"on",
"iyirmi",
"otuz",
"qırx",
"əlli",
"altmış",
"yetmiş",
"səksən",
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/az/stop_words.py | spacy/lang/az/stop_words.py | # Source: https://github.com/eliasdabbas/advertools/blob/master/advertools/stopwords.py
STOP_WORDS = set(
"""
amma
arasında
artıq
ay
az
bax
belə
beş
bilər
bir
biraz
biri
birşey
biz
bizim
bizlər
bu
buna
bundan
bunların
bunu
bunun
buradan
bütün
bəli
bəlkə
bəy
bəzi
bəzən
daha
dedi
deyil
dir
düz
də
dək
dən
dəqiqə
edir
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/bn/tokenizer_exceptions.py | spacy/lang/bn/tokenizer_exceptions.py | from ...symbols import NORM, ORTH
from ...util import update_exc
from ..tokenizer_exceptions import BASE_EXCEPTIONS
_exc = {}
for exc_data in [
{ORTH: "ডঃ", NORM: "ডক্টর"},
{ORTH: "ডাঃ", NORM: "ডাক্তার"},
{ORTH: "ড.", NORM: "ডক্টর"},
{ORTH: "ডা.", NORM: "ডাক্তার"},
{ORTH: "মোঃ", NORM: "মোহাম্মদ"}... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/bn/__init__.py | spacy/lang/bn/__init__.py | from typing import Callable, Optional
from thinc.api import Model
from ...language import BaseDefaults, Language
from ...pipeline import Lemmatizer
from .punctuation import TOKENIZER_INFIXES, TOKENIZER_PREFIXES, TOKENIZER_SUFFIXES
from .stop_words import STOP_WORDS
from .tokenizer_exceptions import TOKENIZER_EXCEPTIO... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/bn/punctuation.py | spacy/lang/bn/punctuation.py | from ..char_classes import (
ALPHA,
ALPHA_LOWER,
CONCAT_QUOTES,
HYPHENS,
LIST_ELLIPSES,
LIST_ICONS,
LIST_PUNCT,
LIST_QUOTES,
UNITS,
)
_currency = r"\$¢£€¥฿৳"
_quotes = CONCAT_QUOTES.replace("'", "")
_list_punct = LIST_PUNCT + "। ॥".strip().split()
_prefixes = [r"\+"] + _list_punct... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/bn/examples.py | spacy/lang/bn/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.bn.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = ["তুই খুব ভালো", "আজ আমরা ডাক্তার দেখতে যাবো", "আমি জানি না "]
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/bn/stop_words.py | spacy/lang/bn/stop_words.py | STOP_WORDS = set(
"""
অতএব অথচ অথবা অনুযায়ী অনেক অনেকে অনেকেই অন্তত অবধি অবশ্য অর্থাৎ অন্য অনুযায়ী অর্ধভাগে
আগামী আগে আগেই আছে আজ আদ্যভাগে আপনার আপনি আবার আমরা আমাকে আমাদের আমার আমি আর আরও
ইত্যাদি ইহা
উচিত উনি উপর উপরে উত্তর
এ এঁদের এঁরা এই এক একই একজন একটা একটি একবার একে এখন এখনও এখানে এখানেই এটা এসো
এটাই এটি ... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ms/_tokenizer_exceptions_list.py | spacy/lang/ms/_tokenizer_exceptions_list.py | # from https://prpm.dbp.gov.my/cari1?keyword=
# dbp https://en.wikipedia.org/wiki/Dewan_Bahasa_dan_Pustaka
MS_BASE_EXCEPTIONS = set(
"""
aba-aba
abah-abah
abar-abar
abrit-abritan
abu-abu
abuk-abuk
abun-abun
acak-acak
acak-acakan
acang-acang
aci-aci
aci-acian
aci-acinya
adang-adang
adap-adapan
adik-beradik
aduk-aduk... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ms/tokenizer_exceptions.py | spacy/lang/ms/tokenizer_exceptions.py | from ...symbols import NORM, ORTH
from ...util import update_exc
from ..tokenizer_exceptions import BASE_EXCEPTIONS
from ._tokenizer_exceptions_list import MS_BASE_EXCEPTIONS
# Daftar singkatan dan Akronim dari:
# https://ms.wiktionary.org/wiki/Wiktionary:Senarai_akronim_dan_singkatan
_exc = {}
for orth in MS_BASE_E... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ms/__init__.py | spacy/lang/ms/__init__.py | from ...language import BaseDefaults, Language
from .lex_attrs import LEX_ATTRS
from .punctuation import TOKENIZER_INFIXES, TOKENIZER_PREFIXES, TOKENIZER_SUFFIXES
from .stop_words import STOP_WORDS
from .syntax_iterators import SYNTAX_ITERATORS
from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
class MalayDefault... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ms/punctuation.py | spacy/lang/ms/punctuation.py | from ..char_classes import ALPHA, _currency, _units, merge_chars, split_chars
from ..punctuation import TOKENIZER_INFIXES, TOKENIZER_PREFIXES, TOKENIZER_SUFFIXES
_units = (
_units + "s bit Gbps Mbps mbps Kbps kbps ƒ ppi px "
"Hz kHz MHz GHz mAh "
"ratus rb ribu ribuan "
"juta jt jutaan mill?iar million... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ms/syntax_iterators.py | spacy/lang/ms/syntax_iterators.py | from typing import Iterator, Tuple, Union
from ...errors import Errors
from ...symbols import NOUN, PRON, PROPN
from ...tokens import Doc, Span
def noun_chunks(doclike: Union[Doc, Span]) -> Iterator[Tuple[int, int, int]]:
"""
Detect base noun phrases from a dependency parse. Works on both Doc and Span.
"... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ms/examples.py | spacy/lang/ms/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.ms.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"Malaysia ialah sebuah negara yang terletak di Asia Tenggara.",
"Berapa banyak pelajar yang akan menghadiri majlis perpisahan sekolah?",
"Pengeluar... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ms/lex_attrs.py | spacy/lang/ms/lex_attrs.py | import unicodedata
from ...attrs import IS_CURRENCY, LIKE_NUM
from .punctuation import LIST_CURRENCY
_num_words = [
"kosong",
"satu",
"dua",
"tiga",
"empat",
"lima",
"enam",
"tujuh",
"lapan",
"sembilan",
"sepuluh",
"sebelas",
"belas",
"puluh",
"ratus",
"... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ms/stop_words.py | spacy/lang/ms/stop_words.py | STOP_WORDS = set(
"""
ada adalah adanya adapun agak agaknya agar akan akankah akhir akhiri akhirnya
aku akulah amat amatlah anda andalah antar antara antaranya apa apaan apabila
apakah apalagi apatah artinya asal asalkan atas atau ataukah ataupun awal
awalnya
bagai bagaikan bagaimana bagaimanakah bagaimanapun bagi... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/xx/__init__.py | spacy/lang/xx/__init__.py | from ...language import Language
class MultiLanguage(Language):
"""Language class to be used for models that support multiple languages.
This module allows models to specify their language ID as 'xx'.
"""
lang = "xx"
__all__ = ["MultiLanguage"]
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/xx/examples.py | spacy/lang/xx/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.de.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
# combined examples from de/en/es/fr/it/nl/pl/pt/ru
sentences = [
"Die ganze Stadt ist ein Startup: Shenzhen ist das Silicon Valley für Hardware-Firmen",
"Wie deuts... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/th/tokenizer_exceptions.py | spacy/lang/th/tokenizer_exceptions.py | from ...symbols import ORTH
_exc = {
# หน่วยงานรัฐ / government agency
"กกต.": [{ORTH: "กกต."}],
"กทท.": [{ORTH: "กทท."}],
"กทพ.": [{ORTH: "กทพ."}],
"กบข.": [{ORTH: "กบข."}],
"กบว.": [{ORTH: "กบว."}],
"กปน.": [{ORTH: "กปน."}],
"กปภ.": [{ORTH: "กปภ."}],
"กปส.": [{ORTH: "กปส."}],
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/th/__init__.py | spacy/lang/th/__init__.py | from ...language import BaseDefaults, Language
from ...tokens import Doc
from ...util import DummyTokenizer, load_config_from_str, registry
from ...vocab import Vocab
from .lex_attrs import LEX_ATTRS
from .stop_words import STOP_WORDS
DEFAULT_CONFIG = """
[nlp]
[nlp.tokenizer]
@tokenizers = "spacy.th.ThaiTokenizer"
"... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/th/lex_attrs.py | spacy/lang/th/lex_attrs.py | from ...attrs import LIKE_NUM
_num_words = [
"ศูนย์",
"หนึ่ง",
"สอง",
"สาม",
"สี่",
"ห้า",
"หก",
"เจ็ด",
"แปด",
"เก้า",
"สิบ",
"สิบเอ็ด",
"ยี่สิบ",
"ยี่สิบเอ็ด",
"สามสิบ",
"สามสิบเอ็ด",
"สี่สิบ",
"สี่สิบเอ็ด",
"ห้าสิบ",
"ห้าสิบเอ็ด",
"... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/th/stop_words.py | spacy/lang/th/stop_words.py | STOP_WORDS = set(
"""
ทั้งนี้ ดัง ขอ รวม หลังจาก เป็น หลัง หรือ ๆ เกี่ยวกับ ซึ่งได้แก่ ด้วยเพราะ ด้วยว่า ด้วยเหตุเพราะ
ด้วยเหตุว่า สุดๆ เสร็จแล้ว เช่น เข้า ถ้า ถูก ถึง ต่างๆ ใคร เปิดเผย ครา รือ ตาม ใน ได้แก่ ได้แต่
ได้ที่ ตลอดถึง นอกจากว่า นอกนั้น จริง อย่างดี ส่วน เพียงเพื่อ เดียว จัด ทั้งที ทั้งคน ทั้งตัว ไกลๆ
ถึ... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ta/__init__.py | spacy/lang/ta/__init__.py | from ...language import BaseDefaults, Language
from .lex_attrs import LEX_ATTRS
from .stop_words import STOP_WORDS
class TamilDefaults(BaseDefaults):
lex_attr_getters = LEX_ATTRS
stop_words = STOP_WORDS
class Tamil(Language):
lang = "ta"
Defaults = TamilDefaults
__all__ = ["Tamil"]
| python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ta/examples.py | spacy/lang/ta/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.ta.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"கிறிஸ்துமஸ் மற்றும் இனிய புத்தாண்டு வாழ்த்துக்கள்",
"எனக்கு என் குழந்தைப் பருவம் நினைவிருக்கிறது",
"உங்கள் பெயர் என்ன?",
"ஏறத்தாழ இலங்கைத் தமி... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ta/lex_attrs.py | spacy/lang/ta/lex_attrs.py | from ...attrs import LIKE_NUM
_numeral_suffixes = {"பத்து": "பது", "ற்று": "று", "ரத்து": "ரம்", "சத்து": "சம்"}
_num_words = [
"பூச்சியம்",
"ஒரு",
"ஒன்று",
"இரண்டு",
"மூன்று",
"நான்கு",
"ஐந்து",
"ஆறு",
"ஏழு",
"எட்டு",
"ஒன்பது",
"பத்து",
"பதினொன்று",
"பன்னிரண்டு"... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/ta/stop_words.py | spacy/lang/ta/stop_words.py | # Stop words
STOP_WORDS = set(
"""
ஒரு
என்று
மற்றும்
இந்த
இது
என்ற
கொண்டு
என்பது
பல
ஆகும்
அல்லது
அவர்
நான்
உள்ள
அந்த
இவர்
என
முதல்
என்ன
இருந்து
சில
என்
போன்ற
வேண்டும்
வந்து
இதன்
அது
அவன்
தான்
பலரும்
என்னும்
மேலும்
பின்னர்
கொண்ட
இருக்கும்
தனது
உள்ளது
போது
என்றும்
அதன்
தன்
பிறகு
அவர்கள்
வரை
அவள்
நீ
ஆகிய
இருந்தது
உள்... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/fi/tokenizer_exceptions.py | spacy/lang/fi/tokenizer_exceptions.py | from ...symbols import NORM, ORTH
from ...util import update_exc
from ..tokenizer_exceptions import BASE_EXCEPTIONS
_exc = {}
# Source https://www.cs.tut.fi/~jkorpela/kielenopas/5.5.html
for exc_data in [
{ORTH: "aik."},
{ORTH: "alk."},
{ORTH: "alv."},
{ORTH: "ark."},
{ORTH: "as."},
{ORTH: "e... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/fi/__init__.py | spacy/lang/fi/__init__.py | from ...language import BaseDefaults, Language
from .lex_attrs import LEX_ATTRS
from .punctuation import TOKENIZER_INFIXES, TOKENIZER_SUFFIXES
from .stop_words import STOP_WORDS
from .syntax_iterators import SYNTAX_ITERATORS
from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
class FinnishDefaults(BaseDefaults):
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/fi/punctuation.py | spacy/lang/fi/punctuation.py | from ..char_classes import (
ALPHA,
ALPHA_LOWER,
ALPHA_UPPER,
CONCAT_QUOTES,
LIST_ELLIPSES,
LIST_HYPHENS,
LIST_ICONS,
)
from ..punctuation import TOKENIZER_SUFFIXES
_quotes = CONCAT_QUOTES.replace("'", "")
DASHES = "|".join(x for x in LIST_HYPHENS if x != "-")
_infixes = (
LIST_ELLIPSE... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/fi/syntax_iterators.py | spacy/lang/fi/syntax_iterators.py | from typing import Iterator, Tuple, Union
from ...errors import Errors
from ...symbols import NOUN, PRON, PROPN
from ...tokens import Doc, Span
def noun_chunks(doclike: Union[Doc, Span]) -> Iterator[Tuple[int, int, int]]:
"""Detect base noun phrases from a dependency parse. Works on both Doc and Span."""
lab... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/fi/examples.py | spacy/lang/fi/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.fi.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"Itseajavat autot siirtävät vakuutusvastuun autojen valmistajille",
"San Francisco harkitsee toimitusrobottien liikkumisen kieltämistä jalkakäytävillä",... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/fi/lex_attrs.py | spacy/lang/fi/lex_attrs.py | from ...attrs import LIKE_NUM
_num_words = [
"nolla",
"yksi",
"kaksi",
"kolme",
"neljä",
"viisi",
"kuusi",
"seitsemän",
"kahdeksan",
"yhdeksän",
"kymmenen",
"yksitoista",
"kaksitoista",
"kolmetoista",
"neljätoista",
"viisitoista",
"kuusitoista",
"... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/fi/stop_words.py | spacy/lang/fi/stop_words.py | # Source https://github.com/stopwords-iso/stopwords-fi/blob/master/stopwords-fi.txt
# Reformatted with some minor corrections
STOP_WORDS = set(
"""
aiemmin aika aikaa aikaan aikaisemmin aikaisin aikana aikoina aikoo aikovat
aina ainakaan ainakin ainoa ainoat aiomme aion aiotte aivan ajan alas alemmas
alkuisin alkuu... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/tr/tokenizer_exceptions.py | spacy/lang/tr/tokenizer_exceptions.py | import re
from ...symbols import NORM, ORTH
from ..punctuation import ALPHA, ALPHA_LOWER
_exc = {}
_abbr_period_exc = [
{ORTH: "A.B.D.", NORM: "Amerika"},
{ORTH: "Alb.", NORM: "albay"},
{ORTH: "Ank.", NORM: "Ankara"},
{ORTH: "Ar.Gör."},
{ORTH: "Arş.Gör."},
{ORTH: "Asb.", NORM: "astsubay"},
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/tr/__init__.py | spacy/lang/tr/__init__.py | from ...language import BaseDefaults, Language
from .lex_attrs import LEX_ATTRS
from .stop_words import STOP_WORDS
from .syntax_iterators import SYNTAX_ITERATORS
from .tokenizer_exceptions import TOKEN_MATCH, TOKENIZER_EXCEPTIONS
class TurkishDefaults(BaseDefaults):
tokenizer_exceptions = TOKENIZER_EXCEPTIONS
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/tr/syntax_iterators.py | spacy/lang/tr/syntax_iterators.py | from typing import Iterator, Tuple, Union
from ...errors import Errors
from ...symbols import NOUN, PRON, PROPN
from ...tokens import Doc, Span
def noun_chunks(doclike: Union[Doc, Span]) -> Iterator[Tuple[int, int, int]]:
"""
Detect base noun phrases from a dependency parse. Works on both Doc and Span.
"... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/tr/examples.py | spacy/lang/tr/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.tr.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"Neredesin?",
"Neredesiniz?",
"Bu bir cümledir.",
"Sürücüsüz araçlar sigorta yükümlülüğünü üreticilere kaydırıyor.",
"San Francisco kaldırım... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/tr/lex_attrs.py | spacy/lang/tr/lex_attrs.py | from ...attrs import LIKE_NUM
# Thirteen, fifteen etc. are written separate: on üç
_num_words = [
"bir",
"iki",
"üç",
"dört",
"beş",
"altı",
"yedi",
"sekiz",
"dokuz",
"on",
"yirmi",
"otuz",
"kırk",
"elli",
"altmış",
"yetmiş",
"seksen",
"doksan",
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/tr/stop_words.py | spacy/lang/tr/stop_words.py | # Source: https://github.com/stopwords-iso/stopwords-tr
STOP_WORDS = set(
"""
acaba
acep
adamakıllı
adeta
ait
ama
amma
anca
ancak
arada
artık
aslında
aynen
ayrıca
az
açıkça
açıkçası
bana
bari
bazen
bazı
bazısı
bazısına
bazısında
bazısından
bazısını
bazısının
başkası
başkasına
başkasında
başkasından
başkasını
başkas... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/he/__init__.py | spacy/lang/he/__init__.py | from ...language import BaseDefaults, Language
from .lex_attrs import LEX_ATTRS
from .stop_words import STOP_WORDS
class HebrewDefaults(BaseDefaults):
stop_words = STOP_WORDS
lex_attr_getters = LEX_ATTRS
writing_system = {"direction": "rtl", "has_case": False, "has_letters": True}
class Hebrew(Language)... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/he/examples.py | spacy/lang/he/examples.py | """
Example sentences to test spaCy and its language models.
>>> from spacy.lang.he.examples import sentences
>>> docs = nlp.pipe(sentences)
"""
sentences = [
"סין מקימה קרן של 440 מיליון דולר להשקעה בהייטק בישראל",
'רה"מ הודיע כי יחרים טקס בחסותו',
"הכנסת צפויה לאשר איכון אוטומטי של שיחות למוקד 100",
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/he/lex_attrs.py | spacy/lang/he/lex_attrs.py | from ...attrs import LIKE_NUM
_num_words = [
"אפס",
"אחד",
"אחת",
"שתיים",
"שתים",
"שניים",
"שנים",
"שלוש",
"שלושה",
"ארבע",
"ארבעה",
"חמש",
"חמישה",
"שש",
"שישה",
"שבע",
"שבעה",
"שמונה",
"תשע",
"תשעה",
"עשר",
"עשרה",
"אחד עשר"... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/he/stop_words.py | spacy/lang/he/stop_words.py | STOP_WORDS = set(
"""
אני
את
אתה
אנחנו
אתן
אתם
הם
הן
היא
הוא
שלי
שלו
שלך
שלה
שלנו
שלכם
שלכן
שלהם
שלהן
לי
לו
לה
לנו
לכם
לכן
להם
להן
אותה
אותו
זה
זאת
אלה
אלו
תחת
מתחת
מעל
בין
עם
עד
על
אל
מול
של
אצל
כמו
אחר
אותו
בלי
לפני
אחרי
מאחורי
עלי
עליו
עליה
עליך
עלינו
עליכם
עליכן
עליהם
עליהן
כל
כולם
כולן
כך
ככה
כזה
כזאת
זה
אותי
... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/uk/tokenizer_exceptions.py | spacy/lang/uk/tokenizer_exceptions.py | from ...symbols import NORM, ORTH
from ...util import update_exc
from ..tokenizer_exceptions import BASE_EXCEPTIONS
_exc = {}
for exc_data in [
{ORTH: "обл.", NORM: "область"},
{ORTH: "р-н.", NORM: "район"},
{ORTH: "р-н", NORM: "район"},
{ORTH: "м.", NORM: "місто"},
{ORTH: "вул.", NORM: "вулиця"},... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
explosion/spaCy | https://github.com/explosion/spaCy/blob/c1e7cb2ebf387a833d56e3b0bee23788d54b1448/spacy/lang/uk/lemmatizer.py | spacy/lang/uk/lemmatizer.py | from typing import Callable, Optional
from thinc.api import Model
from ...pipeline.lemmatizer import lemmatizer_score
from ...vocab import Vocab
from ..ru.lemmatizer import RussianLemmatizer
class UkrainianLemmatizer(RussianLemmatizer):
def __init__(
self,
vocab: Vocab,
model: Optional[M... | python | MIT | c1e7cb2ebf387a833d56e3b0bee23788d54b1448 | 2026-01-04T14:42:48.113774Z | false |
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