



__snake_case    :		Dict  ='Tobias Carryer'

from time import time



class 	lowerCamelCase__      :




		'''simple docstring'''



		def __init__(self		,__lowerCamelCase		,__lowerCamelCase		,__lowerCamelCase		,__lowerCamelCase=int(time()			)			)					->      List[Any]:  # noqa: B008

						"""simple docstring"""






						lowerCAmelCase__					:    Union[str, Any]												=					multiplier
						lowerCAmelCase__					:    int												=					increment
						lowerCAmelCase__					:    Optional[Any]												=					modulo
						lowerCAmelCase__					:    Dict												=					seed



		def 		lowerCAmelCase__				(self			)					->      Union[str, Any]:

						"""simple docstring"""






						lowerCAmelCase__					:    Optional[int]												=					(self.multiplier * self.seed + self.increment) % self.modulo
						return self.seed


if __name__ == "__main__":
							# Show the LCG in action.
							__snake_case    :		Tuple  =LinearCongruentialGenerator(1_6_6_4_5_2_5, 1_0_1_3_9_0_4_2_2_3, 2 << 3_1)
							while True:
														print(lcg.next_number())






from arguments import InitializationArguments

from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser


# Configuration
__snake_case    :		Dict  =HfArgumentParser(InitializationArguments)
__snake_case    :		Tuple  =parser.parse_args()

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

# Config: "scale_attn_by_layer_idx" and "reorder_and_upcast_attn" are Mistral stability tweaks
__snake_case    :		List[str]  ={
    '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    :		List[Any]  =AutoConfig.from_pretrained(args.config_name, **config_kwargs)

# Initialize new model with config
__snake_case    :		int  =AutoModelForCausalLM.from_config(config)

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

