



'''simple docstring'''
from arguments import InitializationArguments

from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser


# Configuration
snake_case_					:      int    			=    HfArgumentParser(InitializationArguments)
snake_case_					:      List[Any]    			=    parser.parse_args()

# Load codeparrot tokenizer trained for Python code tokenization
snake_case_					:      Optional[Any]    			=    AutoTokenizer.from_pretrained(args.tokenizer_name)

# Config: "scale_attn_by_layer_idx" and "reorder_and_upcast_attn" are Mistral stability tweaks
snake_case_					:      Any    			=    {
    'vocab_size': len(tokenizer),
    'scale_attn_by_inverse_layer_idx': True,
    'reorder_and_upcast_attn': True,
}

# Load model config (GPT-2 large in this case)
snake_case_					:      Optional[Any]    			=    AutoConfig.from_pretrained(args.config_name, **config_kwargs)

# Initialize new model with config
snake_case_					:      Optional[int]    			=    AutoModelForCausalLM.from_config(config)

# Save model to the hub
model.save_pretrained(args.model_name, push_to_hub=args.push_to_hub)







'''simple docstring'''
from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


snake_case_					:      List[Any]    			=    {'configuration_van': ['VAN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'VanConfig']}


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_					:      str    			=    [
					    'VAN_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'VanForImageClassification',
					    'VanModel',
					    'VanPreTrainedModel',
					]

if TYPE_CHECKING:
					from .configuration_van import VAN_PRETRAINED_CONFIG_ARCHIVE_MAP, VanConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_van import (
										    VAN_PRETRAINED_MODEL_ARCHIVE_LIST,
										    VanForImageClassification,
										    VanModel,
										    VanPreTrainedModel,
										)

else:
					import sys

					snake_case_					:      List[Any]    			=    _LazyModule(__name__, globals()['__file__'], _import_structure)


