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Attempt at fixing 4-bit with CPU offload
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@ -1,3 +1,4 @@
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import re
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import sys
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from pathlib import Path
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@ -56,16 +57,20 @@ def load_quantized(model_name):
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# Multiple GPUs or GPU+CPU
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if shared.args.gpu_memory:
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memory_map = list(map(lambda x : x.strip(), shared.args.gpu_memory))
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max_cpu_memory = shared.args.cpu_memory.strip() if shared.args.cpu_memory is not None else '99GiB'
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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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for i in range(len(memory_map)):
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max_memory[i] = f'{memory_map[i]}GiB' if not re.match('.*ib$', memory_map[i].lower()) else memory_map[i]
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max_memory['cpu'] = max_cpu_memory
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device_map = accelerate.infer_auto_device_map(model, max_memory=max_memory, no_split_module_classes=["LlamaDecoderLayer"])
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model = accelerate.dispatch_model(model, device_map=device_map)
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print("Using the following device map for the 4-bit model:", device_map)
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# https://huggingface.co/docs/accelerate/package_reference/big_modeling#accelerate.dispatch_model
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model = accelerate.dispatch_model(model, device_map=device_map, offload_buffers=True)
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# Single GPU
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else:
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elif not shared.args.cpu:
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model = model.to(torch.device('cuda:0'))
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return model
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