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Attempt at fixing 4-bit with CPU offload

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oobabooga 2023-03-20 15:11:56 -03:00 committed by GitHub
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commit 9a3bed50c3
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1 changed files with 10 additions and 5 deletions
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15
modules/GPTQ_loader.py
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@ -1,3 +1,4 @@
import re
import sys
from pathlib import Path
@ -56,16 +57,20 @@ def load_quantized(model_name):
# Multiple GPUs or GPU+CPU
if shared.args.gpu_memory:
memory_map = list(map(lambda x : x.strip(), shared.args.gpu_memory))
max_cpu_memory = shared.args.cpu_memory.strip() if shared.args.cpu_memory is not None else '99GiB'
max_memory = {}
for i in range(len(shared.args.gpu_memory)):
max_memory[i] = f"{shared.args.gpu_memory[i]}GiB"
max_memory['cpu'] = f"{shared.args.cpu_memory or '99'}GiB"
for i in range(len(memory_map)):
max_memory[i] = f'{memory_map[i]}GiB' if not re.match('.*ib$', memory_map[i].lower()) else memory_map[i]
max_memory['cpu'] = max_cpu_memory
device_map = accelerate.infer_auto_device_map(model, max_memory=max_memory, no_split_module_classes=["LlamaDecoderLayer"])
model = accelerate.dispatch_model(model, device_map=device_map)
print("Using the following device map for the 4-bit model:", device_map)
# https://huggingface.co/docs/accelerate/package_reference/big_modeling#accelerate.dispatch_model
model = accelerate.dispatch_model(model, device_map=device_map, offload_buffers=True)
# Single GPU
else:
elif not shared.args.cpu:
model = model.to(torch.device('cuda:0'))
return model