Add token arugment in example scripts (#25172)
* fix * fix * fix * fix * fix * fix * fix --------- Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
@@ -21,6 +21,7 @@ import os
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import random
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import sys
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import time
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import warnings
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from dataclasses import asdict, dataclass, field
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from enum import Enum
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from itertools import chain
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@@ -149,15 +150,21 @@ class ModelArguments:
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default="main",
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metadata={"help": "The specific model version to use (can be a branch name, tag name or commit id)."},
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)
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use_auth_token: bool = field(
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default=False,
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token: str = field(
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default=None,
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metadata={
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"help": (
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"Will use the token generated when running `huggingface-cli login` (necessary to use this script "
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"with private models)."
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"The token to use as HTTP bearer authorization for remote files. If not specified, will use the token "
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"generated when running `huggingface-cli login` (stored in `~/.huggingface`)."
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)
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},
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)
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use_auth_token: bool = field(
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default=None,
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metadata={
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"help": "The `use_auth_token` argument is deprecated and will be removed in v4.34. Please use `token`."
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},
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)
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@dataclass
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@@ -377,6 +384,12 @@ def main():
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else:
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model_args, data_args, training_args = parser.parse_args_into_dataclasses()
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if model_args.use_auth_token is not None:
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warnings.warn("The `use_auth_token` argument is deprecated and will be removed in v4.34.", FutureWarning)
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if model_args.token is not None:
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raise ValueError("`token` and `use_auth_token` are both specified. Please set only the argument `token`.")
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model_args.token = model_args.use_auth_token
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# Sending telemetry. Tracking the example usage helps us better allocate resources to maintain them. The
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# information sent is the one passed as arguments along with your Python/PyTorch versions.
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send_example_telemetry("run_ner", model_args, data_args, framework="flax")
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@@ -422,7 +435,7 @@ def main():
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data_args.dataset_name,
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data_args.dataset_config_name,
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cache_dir=model_args.cache_dir,
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use_auth_token=True if model_args.use_auth_token else None,
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token=model_args.token,
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)
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else:
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# Loading the dataset from local csv or json file.
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@@ -436,7 +449,7 @@ def main():
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extension,
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data_files=data_files,
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cache_dir=model_args.cache_dir,
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use_auth_token=True if model_args.use_auth_token else None,
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token=model_args.token,
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)
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# See more about loading any type of standard or custom dataset at
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# https://huggingface.co/docs/datasets/loading_datasets.html.
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@@ -490,7 +503,7 @@ def main():
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finetuning_task=data_args.task_name,
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cache_dir=model_args.cache_dir,
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revision=model_args.model_revision,
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token=True if model_args.use_auth_token else None,
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token=model_args.token,
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)
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tokenizer_name_or_path = model_args.tokenizer_name if model_args.tokenizer_name else model_args.model_name_or_path
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if config.model_type in {"gpt2", "roberta"}:
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@@ -498,7 +511,7 @@ def main():
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tokenizer_name_or_path,
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cache_dir=model_args.cache_dir,
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revision=model_args.model_revision,
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token=True if model_args.use_auth_token else None,
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token=model_args.token,
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add_prefix_space=True,
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)
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else:
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@@ -506,14 +519,14 @@ def main():
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tokenizer_name_or_path,
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cache_dir=model_args.cache_dir,
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revision=model_args.model_revision,
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token=True if model_args.use_auth_token else None,
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token=model_args.token,
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)
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model = FlaxAutoModelForTokenClassification.from_pretrained(
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model_args.model_name_or_path,
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config=config,
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cache_dir=model_args.cache_dir,
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revision=model_args.model_revision,
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token=True if model_args.use_auth_token else None,
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token=model_args.token,
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)
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# Preprocessing the datasets
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