mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-11-23 16:38:21 +01:00
39 lines
1.6 KiB
Python
39 lines
1.6 KiB
Python
'''
|
|
|
|
Converts a transformers model to safetensors format and shards it.
|
|
|
|
This makes it faster to load (because of safetensors) and lowers its RAM usage
|
|
while loading (because of sharding).
|
|
|
|
Based on the original script by 81300:
|
|
|
|
https://gist.github.com/81300/fe5b08bff1cba45296a829b9d6b0f303
|
|
|
|
'''
|
|
|
|
import argparse
|
|
from pathlib import Path
|
|
|
|
import torch
|
|
from transformers import AutoModelForCausalLM, AutoTokenizer
|
|
|
|
parser = argparse.ArgumentParser(formatter_class=lambda prog: argparse.HelpFormatter(prog,max_help_position=54))
|
|
parser.add_argument('MODEL', type=str, default=None, nargs='?', help="Path to the input model.")
|
|
parser.add_argument('--output', type=str, default=None, help='Path to the output folder (default: models/{model_name}_safetensors).')
|
|
parser.add_argument("--max-shard-size", type=str, default="2GB", help="Maximum size of a shard in GB or MB (default: %(default)s).")
|
|
parser.add_argument('--bf16', action='store_true', help='Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU.')
|
|
args = parser.parse_args()
|
|
|
|
if __name__ == '__main__':
|
|
path = Path(args.MODEL)
|
|
model_name = path.name
|
|
|
|
print(f"Loading {model_name}...")
|
|
model = AutoModelForCausalLM.from_pretrained(path, low_cpu_mem_usage=True, torch_dtype=torch.bfloat16 if args.bf16 else torch.float16)
|
|
tokenizer = AutoTokenizer.from_pretrained(path)
|
|
|
|
out_folder = args.output or Path(f"models/{model_name}_safetensors")
|
|
print(f"Saving the converted model to {out_folder} with a maximum shard size of {args.max_shard_size}...")
|
|
model.save_pretrained(out_folder, max_shard_size=args.max_shard_size, safe_serialization=True)
|
|
tokenizer.save_pretrained(out_folder)
|