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@@ -110,7 +110,18 @@ def load_model(model_name):
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exit()
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model = load_quant(path_to_model, Path(f"models/{pt_model}"), 4)
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- model = model.to(torch.device('cuda:0'))
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+
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+ if shared.args.gpu_memory:
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+ max_memory = {}
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+ for i in range(len(shared.args.gpu_memory)):
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+ max_memory[i] = f"{shared.args.gpu_memory[i]}GiB"
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+ max_memory['cpu'] = f"{shared.args.cpu_memory or '99'}GiB"
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+
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+ import accelerate
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+ device_map = accelerate.infer_auto_device_map(model, max_memory=max_memory)
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+ model = accelerate.dispatch_model(model, device_map=device_map)
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+ else:
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+ model = model.to(torch.device('cuda:0'))
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# Custom
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else:
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