|
import os |
|
import glob |
|
from datasets import load_dataset, get_dataset_config_names |
|
from dataclasses import dataclass, field |
|
from transformers import AutoModel, AutoTokenizer, AutoModelForCausalLM, AutoModelForSeq2SeqLM, HfArgumentParser |
|
from typing import Optional, List |
|
|
|
|
|
@dataclass |
|
class DownloadArgs: |
|
model_cache_dir: str = field( |
|
default='/share/LMs', |
|
metadata={'help': 'Default path to save language models'} |
|
) |
|
model_name_or_path: Optional[str] = field( |
|
default=None, |
|
metadata={'help': 'Path to pretrained model or model identifier from huggingface.co/models'} |
|
) |
|
use_lm_class: bool = field( |
|
default=False, |
|
metadata={'help': 'Call .from_pretrained from AutoModelForCausalLM? Useful when downloading remote-code based lms.'} |
|
) |
|
dataset_cache_dir: str = field( |
|
default='/share/peitian/Data/Datasets/huggingface', |
|
metadata={'help': 'Default path to save huggingface datasets'} |
|
) |
|
dataset_name_or_path: Optional[str] = field( |
|
default=None, |
|
metadata={'help': 'Dataset name'} |
|
) |
|
dataset_subset: Optional[str] = field( |
|
default=None, |
|
metadata={'help': 'Dataset subset name'} |
|
) |
|
dataset_split: Optional[str] = field( |
|
default=None, |
|
metadata={'help': 'Dataset split'} |
|
) |
|
|
|
revision: str = field( |
|
default=None, |
|
metadata={'help': 'Remote code revision'} |
|
) |
|
resume_download: bool = field( |
|
default=False, |
|
metadata={'help': 'Resume downloading'} |
|
) |
|
def __post_init__(self): |
|
|
|
if self.model_name_or_path is not None: |
|
kwargs = { |
|
'revision': self.revision, |
|
'resume_download': self.resume_download |
|
} |
|
AutoTokenizer.from_pretrained(self.model_name_or_path, cache_dir=self.model_cache_dir, trust_remote_code=True, **kwargs) |
|
if self.use_lm_class: |
|
AutoModelForCausalLM.from_pretrained(self.model_name_or_path, cache_dir=self.model_cache_dir, trust_remote_code=True, **kwargs) |
|
else: |
|
AutoModel.from_pretrained(self.model_name_or_path, cache_dir=self.model_cache_dir, trust_remote_code=True, **kwargs) |
|
if self.dataset_name_or_path is not None: |
|
if self.dataset_subset is None: |
|
dataset_subsets = get_dataset_config_names(self.dataset_name_or_path) |
|
for dataset_subset in dataset_subsets: |
|
load_dataset(self.dataset_name_or_path, name=dataset_subset, split=self.dataset_split, cache_dir=self.dataset_cache_dir) |
|
else: |
|
load_dataset(self.dataset_name_or_path, name=self.dataset_subset, split=self.dataset_split, cache_dir=self.dataset_cache_dir) |
|
|
|
|
|
if __name__ == "__main__": |
|
parser = HfArgumentParser([DownloadArgs]) |
|
args, = parser.parse_args_into_dataclasses() |
|
|
