2023-03-17 00:35:53 +00:00
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from pathlib import Path
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import modules.shared as shared
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from modules.models import load_model
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def add_lora_to_model(lora_name):
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2023-03-18 13:55:24 +00:00
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from peft import PeftModel
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2023-03-17 00:35:53 +00:00
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# Is there a more efficient way of returning to the base model?
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if lora_name == "None":
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2023-03-17 14:43:11 +00:00
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print("Reloading the model to remove the LoRA...")
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2023-03-17 00:35:53 +00:00
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shared.model, shared.tokenizer = load_model(shared.model_name)
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else:
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2023-03-17 14:39:48 +00:00
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print(f"Adding the LoRA {lora_name} to the model...")
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2023-03-23 03:55:33 +00:00
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2023-03-17 20:45:28 +00:00
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params = {}
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2023-03-23 19:49:41 +00:00
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if not shared.args.cpu:
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2023-03-23 03:55:33 +00:00
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params['dtype'] = shared.model.dtype
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2023-03-23 19:49:41 +00:00
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if hasattr(shared.model, "hf_device_map"):
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params['device_map'] = {"base_model.model."+k: v for k, v in shared.model.hf_device_map.items()}
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elif shared.args.load_in_8bit:
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params['device_map'] = {'': 0}
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2023-03-23 03:55:33 +00:00
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2023-03-17 20:45:28 +00:00
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shared.model = PeftModel.from_pretrained(shared.model, Path(f"loras/{lora_name}"), **params)
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2023-03-23 04:05:13 +00:00
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if not shared.args.load_in_8bit and not shared.args.cpu:
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2023-03-23 03:55:33 +00:00
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shared.model.half()
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2023-03-23 19:49:41 +00:00
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if not hasattr(shared.model, "hf_device_map"):
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shared.model.cuda()
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