2023-03-16 20:35:53 -04:00
|
|
|
from pathlib import Path
|
|
|
|
|
|
|
|
import modules.shared as shared
|
|
|
|
from modules.models import load_model
|
|
|
|
|
|
|
|
|
|
|
|
def add_lora_to_model(lora_name):
|
|
|
|
|
2023-03-18 09:55:24 -04:00
|
|
|
from peft import PeftModel
|
|
|
|
|
2023-03-16 20:35:53 -04:00
|
|
|
# Is there a more efficient way of returning to the base model?
|
|
|
|
if lora_name == "None":
|
2023-03-17 10:43:11 -04:00
|
|
|
print("Reloading the model to remove the LoRA...")
|
2023-03-16 20:35:53 -04:00
|
|
|
shared.model, shared.tokenizer = load_model(shared.model_name)
|
|
|
|
else:
|
2023-03-17 10:39:48 -04:00
|
|
|
print(f"Adding the LoRA {lora_name} to the model...")
|
2023-03-22 23:55:33 -04:00
|
|
|
|
2023-03-17 16:45:28 -04:00
|
|
|
params = {}
|
2023-03-22 23:55:33 -04:00
|
|
|
if shared.args.load_in_8bit:
|
|
|
|
params['device_map'] = {'': 0}
|
|
|
|
else:
|
|
|
|
params['device_map'] = 'auto'
|
|
|
|
params['dtype'] = shared.model.dtype
|
|
|
|
|
2023-03-17 16:45:28 -04:00
|
|
|
shared.model = PeftModel.from_pretrained(shared.model, Path(f"loras/{lora_name}"), **params)
|
2023-03-22 23:55:33 -04:00
|
|
|
if not shared.args.load_in_8bit:
|
|
|
|
shared.model.half()
|