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Add --no_use_cuda_fp16 param for AutoGPTQ

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oobabooga 2023-06-23 12:22:56 -03:00
parent 5646690769
commit 3ae9af01aa
5 changed files with 6 additions and 2 deletions
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3
modules/AutoGPTQ_loader.py
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@ -48,7 +48,8 @@ def load_quantized(model_name):
'use_safetensors': use_safetensors,
'trust_remote_code': shared.args.trust_remote_code,
'max_memory': get_max_memory_dict(),
'quantize_config': quantize_config
'quantize_config': quantize_config,
'use_cuda_fp16': not shared.args.no_use_cuda_fp16,
}
logger.info(f"The AutoGPTQ params are: {params}")

1
modules/loaders.py
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@ -9,6 +9,7 @@ loaders_and_params = {
'triton',
'no_inject_fused_attention',
'no_inject_fused_mlp',
'no_use_cuda_fp16',
'wbits',
'groupsize',
'desc_act',

1
modules/shared.py
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@ -147,6 +147,7 @@ parser.add_argument('--autogptq', action='store_true', help='DEPRECATED')
parser.add_argument('--triton', action='store_true', help='Use triton.')
parser.add_argument('--no_inject_fused_attention', action='store_true', help='Do not use fused attention (lowers VRAM requirements).')
parser.add_argument('--no_inject_fused_mlp', action='store_true', help='Triton mode only: Do not use fused MLP (lowers VRAM requirements).')
parser.add_argument('--no_use_cuda_fp16', action='store_true', help='This can make models faster on some systems.')
parser.add_argument('--desc_act', action='store_true', help='For models that don\'t have a quantize_config.json, this parameter is used to define whether to set desc_act or not in BaseQuantizeConfig.')
# ExLlama

2
modules/ui.py
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@ -30,7 +30,7 @@ theme = gr.themes.Default(
def list_model_elements():
elements = ['loader', 'cpu_memory', 'auto_devices', 'disk', 'cpu', 'bf16', 'load_in_8bit', 'trust_remote_code', 'load_in_4bit', 'compute_dtype', 'quant_type', 'use_double_quant', 'wbits', 'groupsize', 'model_type', 'pre_layer', 'triton', 'desc_act', 'no_inject_fused_attention', 'no_inject_fused_mlp', 'threads', 'n_batch', 'no_mmap', 'mlock', 'n_gpu_layers', 'n_ctx', 'llama_cpp_seed', 'gpu_split']
elements = ['loader', 'cpu_memory', 'auto_devices', 'disk', 'cpu', 'bf16', 'load_in_8bit', 'trust_remote_code', 'load_in_4bit', 'compute_dtype', 'quant_type', 'use_double_quant', 'wbits', 'groupsize', 'model_type', 'pre_layer', 'triton', 'desc_act', 'no_inject_fused_attention', 'no_inject_fused_mlp', 'no_use_cuda_fp16', 'threads', 'n_batch', 'no_mmap', 'mlock', 'n_gpu_layers', 'n_ctx', 'llama_cpp_seed', 'gpu_split']
for i in range(torch.cuda.device_count()):
elements.append(f'gpu_memory_{i}')

1
server.py
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@ -223,6 +223,7 @@ def create_model_menus():
shared.gradio['triton'] = gr.Checkbox(label="triton", value=shared.args.triton)
shared.gradio['no_inject_fused_attention'] = gr.Checkbox(label="no_inject_fused_attention", value=shared.args.no_inject_fused_attention, info='Disable fused attention. Fused attention improves inference performance but uses more VRAM. Disable if running low on VRAM.')
shared.gradio['no_inject_fused_mlp'] = gr.Checkbox(label="no_inject_fused_mlp", value=shared.args.no_inject_fused_mlp, info='Affects Triton only. Disable fused MLP. Fused MLP improves performance but uses more VRAM. Disable if running low on VRAM.')
shared.gradio['no_use_cuda_fp16'] = gr.Checkbox(label="no_use_cuda_fp16", value=shared.args.no_use_cuda_fp16, info='This can make models faster on some systems.')
shared.gradio['desc_act'] = gr.Checkbox(label="desc_act", value=shared.args.desc_act, info='\'desc_act\', \'wbits\', and \'groupsize\' are used for old models without a quantize_config.json.')
shared.gradio['cpu'] = gr.Checkbox(label="cpu", value=shared.args.cpu)
shared.gradio['load_in_8bit'] = gr.Checkbox(label="load-in-8bit", value=shared.args.load_in_8bit)