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Rename --llama-bits to --gptq-bits

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oobabooga 2023-03-12 11:19:07 -03:00
parent fed3617f07
commit 65dda28c9d
3 changed files with 4 additions and 4 deletions
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4
modules/models.py
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@ -42,7 +42,7 @@ def load_model(model_name):
shared.is_RWKV = model_name.lower().startswith('rwkv-') shared.is_RWKV = model_name.lower().startswith('rwkv-')
# Default settings # Default settings
if not any([shared.args.cpu, shared.args.load_in_8bit, shared.args.load_in_4bit, shared.args.llama_bits > 0, shared.args.auto_devices, shared.args.disk, shared.args.gpu_memory is not None, shared.args.cpu_memory is not None, shared.args.deepspeed, shared.args.flexgen, shared.is_RWKV]): if not any([shared.args.cpu, shared.args.load_in_8bit, shared.args.load_in_4bit, shared.args.gptq_bits > 0, shared.args.auto_devices, shared.args.disk, shared.args.gpu_memory is not None, shared.args.cpu_memory is not None, shared.args.deepspeed, shared.args.flexgen, shared.is_RWKV]):
if any(size in shared.model_name.lower() for size in ('13b', '20b', '30b')): if any(size in shared.model_name.lower() for size in ('13b', '20b', '30b')):
model = AutoModelForCausalLM.from_pretrained(Path(f"models/{shared.model_name}"), device_map='auto', load_in_8bit=True) model = AutoModelForCausalLM.from_pretrained(Path(f"models/{shared.model_name}"), device_map='auto', load_in_8bit=True)
else: else:
@ -88,7 +88,7 @@ def load_model(model_name):
return model, tokenizer return model, tokenizer
# 4-bit LLaMA # 4-bit LLaMA
elif shared.args.llama_bits > 0 or shared.args.load_in_4bit: elif shared.args.gptq_bits > 0 or shared.args.load_in_4bit:
from modules.quantized_LLaMA import load_quantized_LLaMA from modules.quantized_LLaMA import load_quantized_LLaMA
model = load_quantized_LLaMA(model_name) model = load_quantized_LLaMA(model_name)

2
modules/quantized_LLaMA.py
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@ -16,7 +16,7 @@ def load_quantized_LLaMA(model_name):
if shared.args.load_in_4bit: if shared.args.load_in_4bit:
bits = 4 bits = 4
else: else:
bits = shared.args.llama_bits bits = shared.args.gptq_bits
path_to_model = Path(f'models/{model_name}') path_to_model = Path(f'models/{model_name}')
pt_model = '' pt_model = ''

2
modules/shared.py
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@ -68,7 +68,7 @@ parser.add_argument('--cai-chat', action='store_true', help='Launch the web UI i
parser.add_argument('--cpu', action='store_true', help='Use the CPU to generate text.') parser.add_argument('--cpu', action='store_true', help='Use the CPU to generate text.')
parser.add_argument('--load-in-8bit', action='store_true', help='Load the model with 8-bit precision.') parser.add_argument('--load-in-8bit', action='store_true', help='Load the model with 8-bit precision.')
parser.add_argument('--load-in-4bit', action='store_true', help='Load the model with 4-bit precision. Currently only works with LLaMA.') parser.add_argument('--load-in-4bit', action='store_true', help='Load the model with 4-bit precision. Currently only works with LLaMA.')
parser.add_argument('--llama-bits', type=int, default=0, help='Load a pre-quantized model with specified precision. 2, 3, 4 and 8bit are supported. Currently only works with LLaMA.') parser.add_argument('--gptq-bits', type=int, default=0, help='Load a pre-quantized model with specified precision. 2, 3, 4 and 8bit are supported. Currently only works with LLaMA.')
parser.add_argument('--bf16', action='store_true', help='Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU.') parser.add_argument('--bf16', action='store_true', help='Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU.')
parser.add_argument('--auto-devices', action='store_true', help='Automatically split the model across the available GPU(s) and CPU.') parser.add_argument('--auto-devices', action='store_true', help='Automatically split the model across the available GPU(s) and CPU.')
parser.add_argument('--disk', action='store_true', help='If the model is too large for your GPU(s) and CPU combined, send the remaining layers to the disk.') parser.add_argument('--disk', action='store_true', help='If the model is too large for your GPU(s) and CPU combined, send the remaining layers to the disk.')