HTh S SK r S SKrS SKJr S SKJrJrJrJrJ r J
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- r*\" \(5 RR S - S- r+\RX " S5 r- " S S5 r. " S S\.5 r/ " S S\.5 r0 " S S\.5 r1S\2S\S 4S jr3S \
\2\4 S\\ 4S jr4S \
\2\4 S \SS4S jr5SS SSSSS!.S"\2S#\2S$\2S%\2S&\2S'\S(\2S)\2S*\\2 S+\6S,\\2 S-\\2 S.\\2 S/\\2 S\4 S0 jjr7\$SS SSSSS SS1.S2\2S3\S4\\2 S5\6S6\\2 S7\\2 S8\\2 S9\\2 S:\6S;\\2 S\24S< jj5 r8g)= N)Path)AnyDictLiteralOptionalTypeUnion)hf_hub_download) upload_file)CardDataDatasetCardData
EvalResult
ModelCardData
SpaceCardDataeval_results_to_model_indexmodel_index_to_eval_results) get_sessionis_jinja_available yaml_dump ) constants)EntryNotFoundError)SoftTemporaryDirectoryloggingvalidate_hf_hub_args templateszmodelcard_template.mdzdatasetcard_template.mdz1^(\s*---[\r\n]+)([\S\s]*?)([\r\n]+---(\r\n|\n|$))c \ rS rSr\r\rSrS S\ S\
4S jjr \ S 5 r
\
R S\ 4S j5 r
S rS \\\ 4 4S
jr\ S S \\ \4 S
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4S jj5 rS S
\\ 4S jjr S S\ S\\ S
\\ S\\ S\\ S\\ S\\
S\\ 4S jjr\ S!S\S\\ S\\ 4S jj5 rS rg )"RepoCard& modelcontentignore_metadata_errorsc X l Xl g)a Initialize a RepoCard from string content. The content should be a
Markdown file with a YAML block at the beginning and a Markdown body.
Args:
content (`str`): The content of the Markdown file.
Example:
```python
>>> from huggingface_hub.repocard import RepoCard
>>> text = '''
... ---
... language: en
... license: mit
... ---
...
... # My repo
... '''
>>> card = RepoCard(text)
>>> card.data.to_dict()
{'language': 'en', 'license': 'mit'}
>>> card.text
'\n# My repo\n'
```
Raises the following error:
- [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
when the content of the repo card metadata is not a dictionary.
N)r" r! )selfr! r" s P/var/www/auris/envauris/lib/python3.13/site-packages/huggingface_hub/repocard.py__init__RepoCard.__init__+ s H '=# c [ U R 5 =( d SnSU U R R XR S9 U SU U R
3$ )zLThe content of the RepoCard, including the YAML block and the Markdown body.
---)
line_breakoriginal_order)_detect_line_ending_contentdatato_yaml_original_ordertext)r$ r, s r% r! RepoCard.contentR sz ) 7?4
ZL!2!2jYmYm!2!n opzo{{~ @J K LP LU LU KV W Wr( c Xl [ R U5 nU( ad UR S5 nXR 5 S U l [ R " U5 nUc 0 n[ U[ 5 ( d [ S5 eO [ R S5 0 nXl U R " S0 UDSU R 0D6U l [! UR# 5 5 U l g)z Set the content of the RepoCard. N)repo card metadata block should be a dictzBRepo card metadata block was not found. Setting CardData to empty.r" )r/ REGEX_YAML_BLOCKsearchgroupendr3 yaml safe_load
isinstancedict
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''0 Q J
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NN_ `I I((i9iTMhMhi #INN$4 5 r( c U R $ N)r! )r$ s r% __str__RepoCard.__str__s s ||r( filepathc [ U5 nUR R SSS9 [ USSSS9 nUR [ U 5 5 SSS5 g! , ( d f g= f)a3 Save a RepoCard to a file.
Args:
filepath (`Union[Path, str]`): Filepath to the markdown file to save.
Example:
```python
>>> from huggingface_hub.repocard import RepoCard
>>> card = RepoCard("---\nlanguage: en\n---\n# This is a test repo card")
>>> card.save("/tmp/test.md")
```
T)parentsexist_okw utf-8modenewlineencodingN)r parentmkdiropenwritestr)r$ rN fs r% save
RepoCard.savev sQ > dT :
(b7
Cq
GGCI D
C
Cs A
A$Nrepo_id_or_path repo_typetokenc [ U5 R 5 ( a [ U5 nO[[ U[ 5 ( a7 [ [ U[
R U=( d U R US95 nO[ SU S35 eUR SSSS9 nU " UR 5 US9sS S S 5 $ ! , ( d f g = f)
a Initialize a RepoCard from a Hugging Face Hub repo's README.md or a local filepath.
Args:
repo_id_or_path (`Union[str, Path]`):
The repo ID associated with a Hugging Face Hub repo or a local filepath.
repo_type (`str`, *optional*):
The type of Hugging Face repo to push to. Defaults to None, which will use use "model". Other options
are "dataset" and "space". Not used when loading from a local filepath. If this is called from a child
class, the default value will be the child class's `repo_type`.
token (`str`, *optional*):
Authentication token, obtained with `huggingface_hub.HfApi.login` method. Will default to the stored token.
ignore_metadata_errors (`str`):
If True, errors while parsing the metadata section will be ignored. Some information might be lost during
the process. Use it at your own risk.
Returns:
[`huggingface_hub.repocard.RepoCard`]: The RepoCard (or subclass) initialized from the repo's
README.md file or filepath.
Example:
```python
>>> from huggingface_hub.repocard import RepoCard
>>> card = RepoCard.load("nateraw/food")
>>> assert card.data.tags == ["generated_from_trainer", "image-classification", "pytorch"]
```
)rb rc z.Cannot load RepoCard: path not found on disk (z).rrS rT rU )r" N) r is_filer? r] r
r
REPOCARD_NAMErb rA r[ read)clsra rb rc r" card_pathr^ s r% load
RepoCard.load s H ( ( * * _-I
-
- # ++ ' 83== I MoM^^` ab b ^^b7^
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Cc > U=( d U R nU[ U 5 S.nSS0n [ 5 R SX#S9nUR 5 g! [
R R a, nWR S:X a [ UR 5 eUeSnAff = f)a Validates card against Hugging Face Hub's card validation logic.
Using this function requires access to the internet, so it is only called
internally by [`huggingface_hub.repocard.RepoCard.push_to_hub`].
Args:
repo_type (`str`, *optional*, defaults to "model"):
The type of Hugging Face repo to push to. Options are "model", "dataset", and "space".
If this function is called from a child class, the default will be the child class's `repo_type`.
Raises the following errors:
- [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
if the card fails validation checks.
- [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
if the request to the Hub API fails for any other reason.
)repoTyper! Acceptz
text/plainz(https://huggingface.co/api/validate-yaml)headersi N) rb r] r postraise_for_statusrequests
exceptions HTTPError status_coderA r3 )r$ rb bodyrp re excs r% validateRepoCard.validate s , / "4y
\*
""#Mt"eA
"",, }}# (( s (A B 0'BB repo_idcommit_messagecommit_descriptionrevision create_pr
parent_commitc V U=( d U R nU R US9 [ 5 n [ U 5 [ R
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[ U 5 5 [ [ U
5 [ R
UUUUUUUUS9
n SSS5 U $ ! , ( d f W $ = f)aq Push a RepoCard to a Hugging Face Hub repo.
Args:
repo_id (`str`):
The repo ID of the Hugging Face Hub repo to push to. Example: "nateraw/food".
token (`str`, *optional*):
Authentication token, obtained with `huggingface_hub.HfApi.login` method. Will default to
the stored token.
repo_type (`str`, *optional*, defaults to "model"):
The type of Hugging Face repo to push to. Options are "model", "dataset", and "space". If this
function is called by a child class, it will default to the child class's `repo_type`.
commit_message (`str`, *optional*):
The summary / title / first line of the generated commit.
commit_description (`str`, *optional*)
The description of the generated commit.
revision (`str`, *optional*):
The git revision to commit from. Defaults to the head of the `"main"` branch.
create_pr (`bool`, *optional*):
Whether or not to create a Pull Request with this commit. Defaults to `False`.
parent_commit (`str`, *optional*):
The OID / SHA of the parent commit, as a hexadecimal string. Shorthands (7 first characters) are also supported.
If specified and `create_pr` is `False`, the commit will fail if `revision` does not point to `parent_commit`.
If specified and `create_pr` is `True`, the pull request will be created from `parent_commit`.
Specifying `parent_commit` ensures the repo has not changed before committing the changes, and can be
especially useful if the repo is updated / committed to concurrently.
Returns:
`str`: URL of the commit which updated the card metadata.
)rb )
path_or_fileobj path_in_repor{ rc rb r| r} r r~ r N) rb ry r r r rg
write_textr] r ) r$ r{ rc rb r| r} r~ r r tmpdirtmp_pathurls r% push_to_hubRepoCard.push_to_hub s R /
*
#
%F|i&=&==H D * #H
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&
%
s A B
B( card_data
template_path template_strc [ 5 ( a SSKnO [ S5 eUR 5 R 5 nUR U5 Ub [
U5 R 5 nUc# [
U R 5 R 5 nUR U5 nUR " SSUR 5 0UD6nU " U5 $ )a Initialize a RepoCard from a template. By default, it uses the default template.
Templates are Jinja2 templates that can be customized by passing keyword arguments.
Args:
card_data (`huggingface_hub.CardData`):
A huggingface_hub.CardData instance containing the metadata you want to include in the YAML
header of the repo card on the Hugging Face Hub.
template_path (`str`, *optional*):
A path to a markdown file with optional Jinja template variables that can be filled
in with `template_kwargs`. Defaults to the default template.
Returns:
[`huggingface_hub.repocard.RepoCard`]: A RepoCard instance with the specified card data and content from the
template.
r NzjUsing RepoCard.from_template requires Jinja2 to be installed. Please install it with `pip install Jinja2`.r r8 ) r jinja2 ImportErrorto_dictcopyupdater read_textdefault_template_pathTemplaterenderr1 ) ri r r r template_kwargsr kwargstemplater! s r%
from_templateRepoCard.from_template& s 0 9
""$))+
o& $
.88:L 9 9:DDFL??<0//JI,=,=,?J6J7|r( )r/ r2 r! r0 r" r3 )F)NNFrK )NNNNNNNNN)__name__
__module__ __qualname____firstlineno__r rD TEMPLATE_MODELCARD_PATHr rb r] boolr& propertyr! setterrL r r r_ classmethodr rk ry r r __static_attributes__r8 r( r% r r & s O 3I% % T % N W W
^^6s 6 64 U49 - ( $( #', 3P sDy)3P C=3P } 3P
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!
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= 3-= D>= }=~ (,&* ( ( }( sm ( ( r( r c b ^ \ rS rSr\r\rSr\ SS\S\
\ S\
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U =r$ ) ModelCardiR r r r r c ( > [ TU ] " XU40 UD6$ )a5 Initialize a ModelCard from a template. By default, it uses the default template, which can be found here:
https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md
Templates are Jinja2 templates that can be customized by passing keyword arguments.
Args:
card_data (`huggingface_hub.ModelCardData`):
A huggingface_hub.ModelCardData instance containing the metadata you want to include in the YAML
header of the model card on the Hugging Face Hub.
template_path (`str`, *optional*):
A path to a markdown file with optional Jinja template variables that can be filled
in with `template_kwargs`. Defaults to the default template.
Returns:
[`huggingface_hub.ModelCard`]: A ModelCard instance with the specified card data and content from the
template.
Example:
```python
>>> from huggingface_hub import ModelCard, ModelCardData, EvalResult
>>> # Using the Default Template
>>> card_data = ModelCardData(
... language='en',
... license='mit',
... library_name='timm',
... tags=['image-classification', 'resnet'],
... datasets=['beans'],
... metrics=['accuracy'],
... )
>>> card = ModelCard.from_template(
... card_data,
... model_description='This model does x + y...'
... )
>>> # Including Evaluation Results
>>> card_data = ModelCardData(
... language='en',
... tags=['image-classification', 'resnet'],
... eval_results=[
... EvalResult(
... task_type='image-classification',
... dataset_type='beans',
... dataset_name='Beans',
... metric_type='accuracy',
... metric_value=0.9,
... ),
... ],
... model_name='my-cool-model',
... )
>>> card = ModelCard.from_template(card_data)
>>> # Using a Custom Template
>>> card_data = ModelCardData(
... language='en',
... tags=['image-classification', 'resnet']
... )
>>> card = ModelCard.from_template(
... card_data=card_data,
... template_path='./src/huggingface_hub/templates/modelcard_template.md',
... custom_template_var='custom value', # will be replaced in template if it exists
... )
```
superr ri r r r r __class__s r% r ModelCard.from_templateW s R w$Y|___r( r8 r )r r r r r rD r r rb r r r] r r
__classcell__r s @r% r r R s[ #O 3I (,&* H` H` }H` sm H` H`r( r c b ^ \ rS rSr\r\rSr\ SS\S\
\ S\
\ 4U 4S jjj5 r Sr
U =r$ ) DatasetCardi datasetr r r c ( > [ TU ] " XU40 UD6$ )ad Initialize a DatasetCard from a template. By default, it uses the default template, which can be found here:
https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md
Templates are Jinja2 templates that can be customized by passing keyword arguments.
Args:
card_data (`huggingface_hub.DatasetCardData`):
A huggingface_hub.DatasetCardData instance containing the metadata you want to include in the YAML
header of the dataset card on the Hugging Face Hub.
template_path (`str`, *optional*):
A path to a markdown file with optional Jinja template variables that can be filled
in with `template_kwargs`. Defaults to the default template.
Returns:
[`huggingface_hub.DatasetCard`]: A DatasetCard instance with the specified card data and content from the
template.
Example:
```python
>>> from huggingface_hub import DatasetCard, DatasetCardData
>>> # Using the Default Template
>>> card_data = DatasetCardData(
... language='en',
... license='mit',
... annotations_creators='crowdsourced',
... task_categories=['text-classification'],
... task_ids=['sentiment-classification', 'text-scoring'],
... multilinguality='monolingual',
... pretty_name='My Text Classification Dataset',
... )
>>> card = DatasetCard.from_template(
... card_data,
... pretty_name=card_data.pretty_name,
... )
>>> # Using a Custom Template
>>> card_data = DatasetCardData(
... language='en',
... license='mit',
... )
>>> card = DatasetCard.from_template(
... card_data=card_data,
... template_path='./src/huggingface_hub/templates/datasetcard_template.md',
... custom_template_var='custom value', # will be replaced in template if it exists
... )
```
r r s r% r DatasetCard.from_template s r w$Y|___r( r8 r )r r r r r
rD TEMPLATE_DATASETCARD_PATHr rb r r r] r r r r s @r% r r sV %O 5I (,&* 8`"8` }8` sm 8` 8`r( r c \ rS rSr\r\rSrSr g) SpaceCardi spacer8 N)
r r r r r rD r r rb r r8 r( r% r r s #O 3Ir( r r! return)
r*
Nc U R S5 nU R S5 nU R S5 nX- S:X a gX1:X a X2:X a gX: a gg)zDetect the line ending of a string. Used by RepoCard to avoid making huge diff on newlines.
Uses same implementation as in Hub server, keep it in sync.
Returns:
str: The detected line ending of the string.
r r* r r N)count)r! crlfcrlfs r% r. r. sQ
t B t B == D w!| zdj wr(
local_pathc [ U 5 R 5 n[ R U5 nU( aL UR S5 n[
R " U5 nUb [ U[ 5 ( a U$ [ S5 eg )Nr6 r7 )
r r r9 r: r; r= r> r? r@ rA )r r! rG rH r0 s r%
metadata_loadr sh : ((*G # #G ,E [[^
~~j) <:dD11KDEEr( r0 c SnSn[ R R U 5 ( a [ U SSSS9 nUR 5 n[ UR [ 5 ( a UR S nO+[ UR [ 5 ( a UR nSSS5 [ U SSSS9 n[ US US
9n[ R U5 nU( a2 USUR 5 S U U S U 3- X6R 5 S - nO S U U S U U 3nUR U5 UR 5 SSS5 g! , ( d f N= f! , ( d f g= f) a
Save the metadata dict in the upper YAML part Trying to preserve newlines as
in the existing file. Docs about open() with newline="" parameter:
https://docs.python.org/3/library/functions.html?highlight=open#open Does
not work with "^M" linebreaks, which are replaced by
r* rS re utf8)rW rX r NrR F) sort_keysr, r+ )ospathexistsr[ rh r? newlinestupler] r r9 r: startr< r\ close)r r0 r, r! readme data_yamlrG outputs r%
metadata_saver s6 JG ww~~j!!
*c2
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< ; @
?
< ;s A+E4BE
E
E#F)metrics_configmetrics_verifieddataset_config
dataset_splitdataset_revisionmetrics_verification_tokenmodel_pretty_nametask_pretty_nametask_idmetrics_pretty_name
metrics_id
metrics_valuedataset_pretty_name
dataset_idr r r r r r c B S[ U [ UUUUUUUUU U
U
U U S9
/S90$ )u
Creates a metadata dict with the result from a model evaluated on a dataset.
Args:
model_pretty_name (`str`):
The name of the model in natural language.
task_pretty_name (`str`):
The name of a task in natural language.
task_id (`str`):
Example: automatic-speech-recognition. A task id.
metrics_pretty_name (`str`):
A name for the metric in natural language. Example: Test WER.
metrics_id (`str`):
Example: wer. A metric id from https://hf.co/metrics.
metrics_value (`Any`):
The value from the metric. Example: 20.0 or "20.0 ± 1.2".
dataset_pretty_name (`str`):
The name of the dataset in natural language.
dataset_id (`str`):
Example: common_voice. A dataset id from https://hf.co/datasets.
metrics_config (`str`, *optional*):
The name of the metric configuration used in `load_metric()`.
Example: bleurt-large-512 in `load_metric("bleurt", "bleurt-large-512")`.
metrics_verified (`bool`, *optional*, defaults to `False`):
Indicates whether the metrics originate from Hugging Face's [evaluation service](https://huggingface.co/spaces/autoevaluate/model-evaluator) or not. Automatically computed by Hugging Face, do not set.
dataset_config (`str`, *optional*):
Example: fr. The name of the dataset configuration used in `load_dataset()`.
dataset_split (`str`, *optional*):
Example: test. The name of the dataset split used in `load_dataset()`.
dataset_revision (`str`, *optional*):
Example: 5503434ddd753f426f4b38109466949a1217c2bb. The name of the dataset dataset revision
used in `load_dataset()`.
metrics_verification_token (`bool`, *optional*):
A JSON Web Token that is used to verify whether the metrics originate from Hugging Face's [evaluation service](https://huggingface.co/spaces/autoevaluate/model-evaluator) or not.
Returns:
`dict`: a metadata dict with the result from a model evaluated on a dataset.
Example:
```python
>>> from huggingface_hub import metadata_eval_result
>>> results = metadata_eval_result(
... model_pretty_name="RoBERTa fine-tuned on ReactionGIF",
... task_pretty_name="Text Classification",
... task_id="text-classification",
... metrics_pretty_name="Accuracy",
... metrics_id="accuracy",
... metrics_value=0.2662102282047272,
... dataset_pretty_name="ReactionJPEG",
... dataset_id="julien-c/reactionjpeg",
... dataset_config="default",
... dataset_split="test",
... )
>>> results == {
... 'model-index': [
... {
... 'name': 'RoBERTa fine-tuned on ReactionGIF',
... 'results': [
... {
... 'task': {
... 'type': 'text-classification',
... 'name': 'Text Classification'
... },
... 'dataset': {
... 'name': 'ReactionJPEG',
... 'type': 'julien-c/reactionjpeg',
... 'config': 'default',
... 'split': 'test'
... },
... 'metrics': [
... {
... 'type': 'accuracy',
... 'value': 0.2662102282047272,
... 'name': 'Accuracy',
... 'verified': False
... }
... ]
... }
... ]
... }
... ]
... }
True
```
model-index)
task_name task_type metric_name metric_type metric_value dataset_name dataset_type
metric_configverified verify_tokenr r r )
model_name eval_results)r r )r r r r r r r r r r r r r r s r% metadata_eval_resultr , sQ R 2( . % 3 *!.!4!+"0 -!;#1"/%5
r( )rb overwriterc r| r} r~ r r r{ metadatarb r rc r| r} r~ r r c Ub UOSnUb US:X a [ n
O(US:X a [ n
OUS:X a [ n
O[ SU 35 e U
R XUS9n UR 5 GH u pU S:X Ga= S U
S
; a [ U S U 5 U
S
S ' [ U
5 u pU R R c" XR l XR l
Mo U R R nU H nS nU H nUR U5 ( d M UU:w a- U( d& [ S
UR SUR S35 eSnUR" Ul UR$ SL d Mr UR& Ul M U( a M U R R R) U5 M GMJ U R R+ U 5 b5 U( d. U R R+ U 5 U
:w a [ SU S35 eXR U ' GM U R- U UUUUUUU S9$ ! [
a. US:X a [ S5 eU
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[ 5 5 n GN f = f)a
Updates the metadata in the README.md of a repository on the Hugging Face Hub.
If the README.md file doesn't exist yet, a new one is created with metadata and an
the default ModelCard or DatasetCard template. For `space` repo, an error is thrown
as a Space cannot exist without a `README.md` file.
Args:
repo_id (`str`):
The name of the repository.
metadata (`dict`):
A dictionary containing the metadata to be updated.
repo_type (`str`, *optional*):
Set to `"dataset"` or `"space"` if updating to a dataset or space,
`None` or `"model"` if updating to a model. Default is `None`.
overwrite (`bool`, *optional*, defaults to `False`):
If set to `True` an existing field can be overwritten, otherwise
attempting to overwrite an existing field will cause an error.
token (`str`, *optional*):
The Hugging Face authentication token.
commit_message (`str`, *optional*):
The summary / title / first line of the generated commit. Defaults to
`f"Update metadata with huggingface_hub"`
commit_description (`str` *optional*)
The description of the generated commit
revision (`str`, *optional*):
The git revision to commit from. Defaults to the head of the
`"main"` branch.
create_pr (`boolean`, *optional*):
Whether or not to create a Pull Request from `revision` with that commit.
Defaults to `False`.
parent_commit (`str`, *optional*):
The OID / SHA of the parent commit, as a hexadecimal string. Shorthands (7 first characters) are also supported.
If specified and `create_pr` is `False`, the commit will fail if `revision` does not point to `parent_commit`.
If specified and `create_pr` is `True`, the pull request will be created from `parent_commit`.
Specifying `parent_commit` ensures the repo has not changed before committing the changes, and can be
especially useful if the repo is updated / committed to concurrently.
Returns:
`str`: URL of the commit which updated the card metadata.
Example:
```python
>>> from huggingface_hub import metadata_update
>>> metadata = {'model-index': [{'name': 'RoBERTa fine-tuned on ReactionGIF',
... 'results': [{'dataset': {'name': 'ReactionGIF',
... 'type': 'julien-c/reactiongif'},
... 'metrics': [{'name': 'Recall',
... 'type': 'recall',
... 'value': 0.7762102282047272}],
... 'task': {'name': 'Text Classification',
... 'type': 'text-classification'}}]}]}
>>> url = metadata_update("hf-internal-testing/reactiongif-roberta-card", metadata)
```
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