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55
main.py
55
main.py
@@ -58,52 +58,29 @@ ACCOUNTS: List[Tuple[str, str, str]] = [
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# 各 GPU 的模型列表(来自 filter_verified_models 脚本的筛选结果)
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# ══════════════════════════════════════════════════════════
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METAX_MODELS = [
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"AI-ModelScope/ip-composition-adapter",
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"AI-ModelScope/stable-diffusion-2-1-base",
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"AI-ModelScope/t2iadapter_color_sd14v1",
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"fpadovani/dan-latn-10mb-after-ppt-shuff-dyck-10mb-ckpt500_seed3407",
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"FutureWater/FST-ET1-14B",
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"okwinds/Rombos-LLM-V2.6-Qwen-14b",
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]
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KUNLUNXIN_MODELS = [
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"futuredatascience/action-classifier-v0",
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"futuredatascience/to-classifier-v0",
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"Wheatley961/Raw_2_no_3_Test_2_new.model",
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"Wheatley961/Raw_2_no_2_Test_2_new.model",
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"Wheatley961/Raw_2_no_0_Test_2_new.model",
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"Wheatley961/Raw_1_no_3_Test_2_new.model",
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"Wheatley961/Raw_1_no_2_Test_2_new.model",
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"Wheatley961/Raw_1_no_1_Test_2_new.model",
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"fpadovani/dan-latn-10mb-after-ppt-shuff-dyck-10mb-ckpt500_seed3407",
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]
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BIREN_MODELS = [
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"utter-project/EuroMoE-2.6B-A0.6B-Instruct-2512",
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"pei39/iol-qwen2.5-14b-sft-awq",
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"hhhar/Linguist_should_be_smart_2",
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"oopere/SmolLM2-1.7B-ClinicalNER",
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"excepto64/lox_SmolLM2-360M_hhrlhf_r0_1e",
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"Maybe1407/harry_phi_to_unlearn",
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"vinayp27/smollm3-medical",
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"FutureWater/FST-ET1-14B",
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"okwinds/Rombos-LLM-V2.6-Qwen-14b",
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]
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CAMBRICON_MODELS = [
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"futuredatascience/action-classifier-v0",
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"futuredatascience/to-classifier-v0",
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"Wheatley961/Raw_2_no_3_Test_2_new.model",
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"Wheatley961/Raw_2_no_1_Test_2_new.model",
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"Wheatley961/Raw_2_no_0_Test_2_new.model",
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"Wheatley961/Raw_1_no_3_Test_2_new.model",
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"Wheatley961/Raw_1_no_2_Test_2_new.model",
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"Wheatley961/Raw_1_no_1_Test_2_new.model",
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"fpadovani/dan-latn-10mb-after-ppt-shuff-dyck-10mb-ckpt500_seed3407",
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]
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HYGON_MODELS = [
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"saidthefox/systema-minion-0.6b-v4",
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"VehaanS/hackathon-250m-precise-edge",
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"futuredatascience/action-classifier-v0",
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"futuredatascience/to-classifier-v0",
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"Wheatley961/Raw_2_no_3_Test_2_new.model",
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"Wheatley961/Raw_2_no_2_Test_2_new.model",
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"Wheatley961/Raw_2_no_1_Test_2_new.model",
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"Wheatley961/Raw_2_no_0_Test_2_new.model",
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"Wheatley961/Raw_1_no_3_Test_2_new.model",
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"Wheatley961/Raw_1_no_2_Test_2_new.model",
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"Wheatley961/Raw_1_no_1_Test_2_new.model",
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"fpadovani/dan-latn-10mb-after-ppt-shuff-dyck-10mb-ckpt500_seed3407",
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]
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MTHREADS_MODELS = [
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@@ -673,11 +650,13 @@ PPU_MODELS = [
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"espressovi/BODHI-qwen-3-maze-8b-distil",
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]
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# 本轮提交第十七轮过滤结果:MetaX_c-500(1) / Kunlunxin_p-800(8) / hygon_k100-ai(11) /
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# Cambricon_mlu-370-x8(8) / Biren_166m(6),共34个;沿用多账号 fallback 轮转;
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# 本轮首次把 Biren_166m 列入 GPU_JOBS;
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# 本轮提交第二十六轮过滤结果:MetaX_c-500(5) / Kunlunxin_p-800(1) / hygon_k100-ai(1) /
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# Cambricon_mlu-370-x8(1) / Biren_166m(3),共11个;沿用多账号 fallback 轮转。
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# 产出为历轮最低:候选池与上轮基本相同,而上轮筛出的84个已在 v1.0.32 全部提交成功并
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# 产生验证记录被排除;需灌入这些卡未跑过的新模型才会有新产出。
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# 本轮不提交 Mthreads_s4000(保留既有列表)/ ppu_zw_810e(机制B无白名单权限)/
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# Sunrise_pt-200-x1(v1.0.13已完成)
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# Sunrise_pt-200-x1(v1.0.13已完成)/
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# Iluvatar_bi-150(本轮筛选为0;且本仓库 framework=vllm,现有 iluvatar 镜像均为 llamacpp/GGUF,缺 vllm 版镜像)
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GPU_JOBS: List[Tuple[str, List[str]]] = [
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("MetaX_c-500", METAX_MODELS),
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("Kunlunxin_p-800", KUNLUNXIN_MODELS),
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