diff --git a/README.md b/README.md index 70f2446c..f7cc95e0 100644 --- a/README.md +++ b/README.md @@ -295,14 +295,15 @@ Optionally, you can use the following command-line flags: | Flag | Description | |---------------|---------------| +| `--mul_mat_q` | Activate new mulmat kernels. | +| `--tensor_split TENSOR_SPLIT` | Split the model across multiple GPUs, comma-separated list of proportions, e.g. 18,17 | +| `--llama_cpp_seed SEED` | Seed for llama-cpp models. Default 0 (random). | +| `--cache-capacity CACHE_CAPACITY` | Maximum cache capacity. Examples: 2000MiB, 2GiB. When provided without units, bytes will be assumed. | +|`--cfg-cache` | llamacpp_HF: Create an additional cache for CFG negative prompts. | | `--no-mmap` | Prevent mmap from being used. | | `--mlock` | Force the system to keep the model in RAM. | -| `--mul_mat_q` | Activate new mulmat kernels. | -| `--cache-capacity CACHE_CAPACITY` | Maximum cache capacity. Examples: 2000MiB, 2GiB. When provided without units, bytes will be assumed. | -| `--tensor_split TENSOR_SPLIT` | Split the model across multiple GPUs, comma-separated list of proportions, e.g. 18,17 | -| `--llama_cpp_seed SEED` | Seed for llama-cpp models. Default 0 (random). | -| `--cpu` | Use the CPU version of llama-cpp-python instead of the GPU-accelerated version. | -|`--cfg-cache` | llamacpp_HF: Create an additional cache for CFG negative prompts. | +| `--numa` | Activate NUMA task allocation for llama.cpp | +| `--cpu` | Use the CPU version of llama-cpp-python instead of the GPU-accelerated version. | #### ctransformers diff --git a/modules/llamacpp_hf.py b/modules/llamacpp_hf.py index 04f1ec85..ff0e8267 100644 --- a/modules/llamacpp_hf.py +++ b/modules/llamacpp_hf.py @@ -172,6 +172,7 @@ class LlamacppHF(PreTrainedModel): @classmethod def from_pretrained(cls, pretrained_model_name_or_path: Optional[Union[str, os.PathLike]], *model_args, **kwargs): assert len(model_args) == 0 and len(kwargs) == 0, "extra args is currently not supported" + if isinstance(pretrained_model_name_or_path, str): pretrained_model_name_or_path = Path(pretrained_model_name_or_path) @@ -198,6 +199,7 @@ class LlamacppHF(PreTrainedModel): 'use_mlock': shared.args.mlock, 'mul_mat_q': shared.args.mul_mat_q, 'low_vram': shared.args.low_vram, + 'numa': shared.args.numa, 'n_gpu_layers': shared.args.n_gpu_layers, 'rope_freq_base': RoPE.get_rope_freq_base(shared.args.alpha_value, shared.args.rope_freq_base), 'tensor_split': tensor_split_list, diff --git a/modules/llamacpp_model.py b/modules/llamacpp_model.py index baacb0b9..febb7229 100644 --- a/modules/llamacpp_model.py +++ b/modules/llamacpp_model.py @@ -81,6 +81,7 @@ class LlamaCppModel: 'use_mlock': shared.args.mlock, 'mul_mat_q': shared.args.mul_mat_q, 'low_vram': shared.args.low_vram, + 'numa': shared.args.numa, 'n_gpu_layers': shared.args.n_gpu_layers, 'rope_freq_base': RoPE.get_rope_freq_base(shared.args.alpha_value, shared.args.rope_freq_base), 'tensor_split': tensor_split_list, diff --git a/modules/loaders.py b/modules/loaders.py index 3104ca56..eec90f46 100644 --- a/modules/loaders.py +++ b/modules/loaders.py @@ -100,6 +100,7 @@ loaders_and_params = OrderedDict({ 'rope_freq_base', 'compress_pos_emb', 'cpu', + 'numa', ], 'llamacpp_HF': [ 'n_ctx', @@ -115,6 +116,7 @@ loaders_and_params = OrderedDict({ 'rope_freq_base', 'compress_pos_emb', 'cpu', + 'numa', 'cfg_cache', 'use_fast', 'llamacpp_HF_info', diff --git a/modules/shared.py b/modules/shared.py index 9b36b2b7..0ca9efb9 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -125,6 +125,7 @@ parser.add_argument('--n-gpu-layers', type=int, default=0, help='Number of layer parser.add_argument('--tensor_split', type=str, default=None, help="Split the model across multiple GPUs, comma-separated list of proportions, e.g. 18,17") parser.add_argument('--n_ctx', type=int, default=2048, help='Size of the prompt context.') parser.add_argument('--llama_cpp_seed', type=int, default=0, help='Seed for llama-cpp models. Default 0 (random)') +parser.add_argument('--numa', action='store_true', help='Activate NUMA task allocation for llama.cpp') # GPTQ parser.add_argument('--wbits', type=int, default=0, help='Load a pre-quantized model with specified precision in bits. 2, 3, 4 and 8 are supported.') diff --git a/modules/ui.py b/modules/ui.py index e4654081..568f0e37 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -82,7 +82,8 @@ def list_model_elements(): 'max_seq_len', 'compress_pos_emb', 'alpha_value', - 'rope_freq_base' + 'rope_freq_base', + 'numa', ] for i in range(torch.cuda.device_count()): diff --git a/modules/ui_model_menu.py b/modules/ui_model_menu.py index a63ad4f9..a2bb1695 100644 --- a/modules/ui_model_menu.py +++ b/modules/ui_model_menu.py @@ -102,6 +102,12 @@ def create_ui(): 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['mul_mat_q'] = gr.Checkbox(label="mul_mat_q", value=shared.args.mul_mat_q, info='Recommended in most cases. Improves generation speed by 10-20%.') + shared.gradio['cfg_cache'] = gr.Checkbox(label="cfg-cache", value=shared.args.cfg_cache, info='Create an additional cache for CFG negative prompts.') + shared.gradio['no_mmap'] = gr.Checkbox(label="no-mmap", value=shared.args.no_mmap) + shared.gradio['mlock'] = gr.Checkbox(label="mlock", value=shared.args.mlock) + shared.gradio['numa'] = gr.Checkbox(label="numa", value=shared.args.numa, info='NUMA support can help on some systems with non-uniform memory access.') + shared.gradio['low_vram'] = gr.Checkbox(label="low-vram", value=shared.args.low_vram) 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) shared.gradio['bf16'] = gr.Checkbox(label="bf16", value=shared.args.bf16) @@ -109,11 +115,6 @@ def create_ui(): shared.gradio['disk'] = gr.Checkbox(label="disk", value=shared.args.disk) shared.gradio['load_in_4bit'] = gr.Checkbox(label="load-in-4bit", value=shared.args.load_in_4bit) shared.gradio['use_double_quant'] = gr.Checkbox(label="use_double_quant", value=shared.args.use_double_quant) - shared.gradio['no_mmap'] = gr.Checkbox(label="no-mmap", value=shared.args.no_mmap) - shared.gradio['low_vram'] = gr.Checkbox(label="low-vram", value=shared.args.low_vram) - shared.gradio['mlock'] = gr.Checkbox(label="mlock", value=shared.args.mlock) - shared.gradio['mul_mat_q'] = gr.Checkbox(label="mul_mat_q", value=shared.args.mul_mat_q, info='Recommended in most cases. Improves generation speed by 10-20%.') - shared.gradio['cfg_cache'] = gr.Checkbox(label="cfg-cache", value=shared.args.cfg_cache, info='Create an additional cache for CFG negative prompts.') shared.gradio['tensor_split'] = gr.Textbox(label='tensor_split', info='Split the model across multiple GPUs, comma-separated list of proportions, e.g. 18,17') shared.gradio['llama_cpp_seed'] = gr.Number(label='Seed (0 for random)', value=shared.args.llama_cpp_seed) shared.gradio['trust_remote_code'] = gr.Checkbox(label="trust-remote-code", value=shared.args.trust_remote_code, info='Make sure to inspect the .py files inside the model folder before loading it with this option enabled.')