SUMIN/HuggingFace_transformer
1
0
Fork 0
Code Issues Pull Requests Actions 7 Packages Projects Releases Wiki Activity

Update use_auth_token -> token in example scripts (#25167)

Browse Source 
* pytorch examples

* tensorflow examples

* flax examples

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Yih-Dar
2023-07-28 15:33:45 +02:00
committed by GitHub
parent 3cbc560d03
commit d53b8ad780
38 changed files with 116 additions and 116 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
examples/pytorch/question-answering/run_qa.py
View File

@@ -322,14 +322,14 @@ def main():
model_args.config_name if model_args.config_name else model_args.model_name_or_path,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
tokenizer = AutoTokenizer.from_pretrained(
model_args.tokenizer_name if model_args.tokenizer_name else model_args.model_name_or_path,
cache_dir=model_args.cache_dir,
use_fast=True,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
model = AutoModelForQuestionAnswering.from_pretrained(
model_args.model_name_or_path,
@@ -337,7 +337,7 @@ def main():
config=config,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
# Tokenizer check: this script requires a fast tokenizer.

6
examples/pytorch/question-answering/run_qa_beam_search.py
View File

@@ -320,13 +320,13 @@ def main():
model_args.config_name if model_args.config_name else model_args.model_name_or_path,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
tokenizer = XLNetTokenizerFast.from_pretrained(
model_args.tokenizer_name if model_args.tokenizer_name else model_args.model_name_or_path,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
model = XLNetForQuestionAnswering.from_pretrained(
model_args.model_name_or_path,
@@ -334,7 +334,7 @@ def main():
config=config,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
# Preprocessing the datasets.

6
examples/pytorch/question-answering/run_seq2seq_qa.py
View File

@@ -367,14 +367,14 @@ def main():
model_args.config_name if model_args.config_name else model_args.model_name_or_path,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
tokenizer = AutoTokenizer.from_pretrained(
model_args.tokenizer_name if model_args.tokenizer_name else model_args.model_name_or_path,
cache_dir=model_args.cache_dir,
use_fast=model_args.use_fast_tokenizer,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
model = AutoModelForSeq2SeqLM.from_pretrained(
model_args.model_name_or_path,
@@ -382,7 +382,7 @@ def main():
config=config,
cache_dir=model_args.cache_dir,
revision=model_args.model_revision,
use_auth_token=True if model_args.use_auth_token else None,
token=True if model_args.use_auth_token else None,
)
# We resize the embeddings only when necessary to avoid index errors. If you are creating a model from scratch