




"""simple docstring"""


from arguments import InitializationArguments

from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser


# Configuration
A_      			=       HfArgumentParser(InitializationArguments)
A_      			=       parser.parse_args()

# Load codeparrot tokenizer trained for Python code tokenization
A_      			=       AutoTokenizer.from_pretrained(args.tokenizer_name)

# Config: "scale_attn_by_layer_idx" and "reorder_and_upcast_attn" are Mistral stability tweaks
A_      			=       {
    '''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)
A_      			=       AutoConfig.from_pretrained(args.config_name, **config_kwargs)

# Initialize new model with config
A_      			=       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 abc import ABC, abstractmethod
from argparse import ArgumentParser






class       lowercase(  __a				):







 '''simple docstring'''





 @staticmethod
 @abstractmethod
 def 				UpperCamelCase_     (       a_:	ArgumentParser	):




   '''simple docstring'''



   raise NotImplementedError()


 @abstractmethod
 def 				UpperCamelCase_     (       self:	List[str]	):




   '''simple docstring'''



   raise NotImplementedError()


