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llama.cpp: Change the default --fit-target from 1024 to 512

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oobabooga 2026-03-15 09:29:25 -07:00
parent 9119ce0680
commit 80d0c03bab
2 changed files with 2 additions and 2 deletions
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2
modules/shared.py
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@ -108,7 +108,7 @@ group.add_argument('--threads', type=int, default=0, help='Number of threads to
group.add_argument('--threads-batch', type=int, default=0, help='Number of threads to use for batches/prompt processing.')
group.add_argument('--numa', action='store_true', help='Activate NUMA task allocation for llama.cpp.')
group.add_argument('--parallel', type=int, default=1, help='Number of parallel request slots. The context size is divided equally among slots. For example, to have 4 slots with 8192 context each, set ctx_size to 32768.')
group.add_argument('--fit-target', type=str, default='1024', help='Target VRAM margin per device for auto GPU layers, comma-separated list of values in MiB. A single value is broadcast across all devices. Default: 1024.')
group.add_argument('--fit-target', type=str, default='512', help='Target VRAM margin per device for auto GPU layers, comma-separated list of values in MiB. A single value is broadcast across all devices.')
group.add_argument('--extra-flags', type=str, default=None, help='Extra flags to pass to llama-server. Format: "flag1=value1,flag2,flag3=value3". Example: "override-tensor=exps=CPU"')
# Transformers/Accelerate

2
modules/ui_model_menu.py
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@ -46,7 +46,7 @@ def create_ui():
shared.gradio['gpu_split'] = gr.Textbox(label='gpu-split', info='Comma-separated list of VRAM (in GB) to use per GPU. Example: 20,7,7')
shared.gradio['attn_implementation'] = gr.Dropdown(label="attn-implementation", choices=['sdpa', 'eager', 'flash_attention_2'], value=shared.args.attn_implementation, info='Attention implementation.')
shared.gradio['cache_type'] = gr.Dropdown(label="cache-type", choices=['fp16', 'q8_0', 'q4_0', 'fp8', 'q8', 'q7', 'q6', 'q5', 'q4', 'q3', 'q2'], value=shared.args.cache_type, allow_custom_value=True, info='Valid options: llama.cpp - fp16, q8_0, q4_0; ExLlamaV3 - fp16, q2 to q8. For ExLlamaV3, you can type custom combinations for separate k/v bits (e.g. q4_q8).')
shared.gradio['fit_target'] = gr.Textbox(label='fit-target', value=shared.args.fit_target, info='Target VRAM margin per device for auto GPU layers (MiB). Comma-separated list for multiple devices. Default: 1024.')
shared.gradio['fit_target'] = gr.Textbox(label='fit-target', value=shared.args.fit_target, info='Target VRAM margin per device for auto GPU layers (MiB). Comma-separated list for multiple devices.')
shared.gradio['tp_backend'] = gr.Dropdown(label="tp-backend", choices=['native', 'nccl'], value=shared.args.tp_backend, info='The backend for tensor parallelism.')
with gr.Column():