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Don't split the layers in 8-bit mode by default

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oobabooga 2023-03-16 18:22:16 -03:00
parent 0a2aa79c4e
commit ee164d1821
1 changed files with 4 additions and 2 deletions
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6
modules/models.py
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@ -105,8 +105,10 @@ def load_model(model_name):
params["torch_dtype"] = torch.float32 params["torch_dtype"] = torch.float32
else: else:
params["device_map"] = 'auto' params["device_map"] = 'auto'
if shared.args.load_in_8bit: if shared.args.load_in_8bit and any((shared.args.auto_devices, shared.args.gpu_memory)):
params['quantization_config'] = BitsAndBytesConfig(load_in_8bit=True, llm_int8_enable_fp32_cpu_offload=True) params['quantization_config'] = BitsAndBytesConfig(load_in_8bit=True, llm_int8_enable_fp32_cpu_offload=True)
elif shared.args.load_in_8bit:
params['quantization_config'] = BitsAndBytesConfig(load_in_8bit=True)
elif shared.args.bf16: elif shared.args.bf16:
params["torch_dtype"] = torch.bfloat16 params["torch_dtype"] = torch.bfloat16
else: else:
@ -119,7 +121,7 @@ def load_model(model_name):
max_memory[i] = f'{memory_map[i]}GiB' max_memory[i] = f'{memory_map[i]}GiB'
max_memory['cpu'] = f'{shared.args.cpu_memory or 99}GiB' max_memory['cpu'] = f'{shared.args.cpu_memory or 99}GiB'
params['max_memory'] = max_memory params['max_memory'] = max_memory
else: elif shared.args.auto_devices:
total_mem = (torch.cuda.get_device_properties(0).total_memory / (1024*1024)) total_mem = (torch.cuda.get_device_properties(0).total_memory / (1024*1024))
suggestion = round((total_mem-1000) / 1000) * 1000 suggestion = round((total_mem-1000) / 1000) * 1000
if total_mem - suggestion < 800: if total_mem - suggestion < 800: