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

from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser


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

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

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

# Initialize new model with config
lowercase__						       =      AutoModelForCausalLM.from_config(config)

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




'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import re

from ..utils import cached_file


# docstyle-ignore
lowercase__						       =      "\nHuman: <<task>>\n\nAssistant: "


lowercase__						       =      "huggingface-tools/default-prompts"
lowercase__						       =      {"chat": "chat_prompt_template.txt", "run": "run_prompt_template.txt"}




def    _UpperCamelCase						(       SCREAMING_SNAKE_CASE__ ,       SCREAMING_SNAKE_CASE__ ,       SCREAMING_SNAKE_CASE__="run"			)  ->							Dict:


		'''simple docstring'''


		if prompt_or_repo_id is None:
				snake_case  :       Union[str, Any]     			=						DEFAULT_PROMPTS_REPO

		# prompt is considered a repo ID when it does not contain any kind of space
		if re.search('''\\s''' ,       SCREAMING_SNAKE_CASE__			) is not None:
				return prompt_or_repo_id

		snake_case  :       List[Any]     			=						cached_file(
		    SCREAMING_SNAKE_CASE__ ,       PROMPT_FILES[mode] ,       repo_type='''dataset''' ,       user_agent={'''agent''': agent_name}			)
		with open(SCREAMING_SNAKE_CASE__ ,       '''r''' ,       encoding='''utf-8'''			) as f:
				return f.read()


