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114
main.py
114
main.py
@@ -58,111 +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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"rombodawg/Rombos-LLM-V2.5-Qwen-32b",
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"Deeptid123/HealthAiAsst-sft-model",
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"athirdpath/Harmonia-20B",
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"kmseong/llama2_7b_base_resta_lr3e-5_y0.3",
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"notshekhar/markdown-1",
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"niljen/xearnes-phi4-mini",
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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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"kmseong/llama2_7b_base_resta_lr3e-5_y0.3",
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"notshekhar/markdown-1",
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"niljen/xearnes-phi4-mini",
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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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"EphemeralYou/Prompt-Refine-MiniCPM5-1B",
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"mtepe01/mentorx-mistral-7b-automata-merged",
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"DarkArtsForge/Helix-SCE-12B-jh",
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"Likithp/v10_fixed_s1",
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"Likithp/v10_rand_s1",
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"ibm-granite/granite-3.3-8b-math-prm-v2",
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"build-small-hackathon/compliment-forest-minicpm5-1b",
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"zenlm/zen3-guard",
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"Likithp/v10_1.5B_fixed_s42",
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"ermiaazarkhalili/Granite-4.1-8B-SFT-Fable5",
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"Mohamed475/qwen3-1.7b-fft-dpo-4epochs",
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"diansm/llm-finetuned-pgabl",
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"NithinAI12/NithinX-Omni-LLM-v1",
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"JoaoZaokk/Qwen3-4B-Thinking-2507-Heretic-CodeFeedback",
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"SamsungSDS-Research/SGuard-JailbreakFilter-2B-v1",
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"ConvexAI/Luminex-34B-v0.2",
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"dipta007/decomposeRL-7b",
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"codellama/CodeLlama-34b-hf",
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"melsmm/Spell-Corrector-RU-4B",
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"vilm/vinallama-7b-chat",
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"Lzvick/qwen-1.7b-math-reasoner-grpo",
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"Lipas007/iol-ai-2026-qwen14b-awq",
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"kosiasuzu/chatml-agent-llama-3.1-8b-init",
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"kosiasuzu/chatml-llama3.1-8b-lora-merged",
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"D-Z-W/finetuned-teacher",
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"hxia7/qwen3-4b-blockdist",
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"ewald1976/MeterMaid-12b",
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"build-small-hackathon/deal_sft_lora_4B",
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"HamnaKaleem/IOL-AI-2026",
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"rae-jax/cie-auditor-final",
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"codingmonster1234/Llama-3.1-Minitron-4B-Chess-Reasoning",
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"modrill/qwen3-4b-think-baseline-lora-sft",
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"Luimas/claim-extractor-detective-qwen3b",
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"modrill/qwen3-4b-nothink-baseline-lora-sft",
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"edusc182/Zen-AI-3B-Full",
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"huan1999/ziya-llama-13b-medical-merged",
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"minhtt/vistral-7b-chat",
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"codellama/CodeLlama-34b-Python-hf",
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"modrill/qwen3-4b-think-baseline-full-sft",
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"kcherry497/dyno-blast-4b",
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"ld4ad/gemma-2-9b-dunhuang",
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"harindhar10/Olmo-7b_1M_Smiles_lora",
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"EthanGao123/CellHermes-v1.0",
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"4dil/coding-architecture-advisor-merged",
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"DavidAU/granite-4.1-8b-Claude-Opus-4.6-Thinking-MAX",
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"Irfanuruchi/Qwen3-4B-Computer-Science",
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"carolinezx/llama-8b-sft-preferred-cleaned",
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"davidanugraha/Qwen3-4B-Instruct-2507-UserSim-SFT-Factored",
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"allenai/Olmo-3-7B-Think-DPO",
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"allenai/Olmo-3-32B-Think-DPO",
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"RedHatAI/gemma-2-9b-it",
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"prashanthsura/gemma-2-2b-legal-financial-sft",
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"pfnet/plamo-2-8b",
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"sail/Sailor2-20B-128K-SFT",
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"facebook/layerskip-llama3.2-1B",
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"Qwen/Qwen2.5-32B",
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"Qwen/Qwen-Image",
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"KordAI/Typhoon-Gemma3-KordTranslate-EN-TH-4B",
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"xiaoqingsun004/Olmo-WildChat",
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"longtermrisk/OLMo-3-7B-target-only-no-hallucination-sft",
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"vimleshiit4463/wyzer-2.0-smollm2-135m",
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"trl-lib/pythia-1b-deduped-tldr-sft",
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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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"kmseong/llama2_7b_base_resta_lr3e-5_y0.3",
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"notshekhar/markdown-1",
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"niljen/xearnes-phi4-mini",
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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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"zwhe99/DeepMath-1.5B",
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"jerchenxin/qwen2.5-Math-1.5B-step-80",
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"jerchenxin/qwen2.5-Math-1.5B-step-1280",
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"ishikauniphore/student_qwen7bins_nemotron_stem_hlrep",
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"GusPuffy/sentient-simulations-pydecompiler-3.7-6.7b-v0.9",
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"neuqrui/safe-rlsd-qwen3-4B",
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"jerchenxin/qwen2.5-Math-1.5B-reinforce_with_baseline-full-step_0000180",
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"oaimli/longtune_scitrek_simple_sft_qwen",
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"jerchenxin/qwen2.5-Math-1.5B-step-1120",
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"jerchenxin/qwen2.5-Math-1.5B-no-baseline-full-step-120",
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"SeongryongJung/Qwen3-4B-Tooluse-RLSD-TR",
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"EPFLiGHT/Meditron3-Qwen2.5-7B",
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"slman4/mistral-nemo-teambrain-merged",
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"OccultAI/Qliphoth-12B-v1.2",
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"Deeptid123/HealthAiAsst-sft-model",
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"Doan2108/contract-risk-qwen2.5-3b-merged",
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"kmseong/llama2_7b_base_resta_lr3e-5_y0.3",
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"notshekhar/markdown-1",
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"niljen/xearnes-phi4-mini",
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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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@@ -732,15 +650,19 @@ PPU_MODELS = [
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"espressovi/BODHI-qwen-3-maze-8b-distil",
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]
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# 本轮提交第十二轮过滤结果:MetaX_c-500(6) / Kunlunxin_p-800(3) / hygon_k100-ai(19) /
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# Cambricon_mlu-370-x8(3),与各卡此前批次均无重复;沿用多账号 fallback 轮转;
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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)/ Biren_166m
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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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("hygon_k100-ai", HYGON_MODELS),
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("Cambricon_mlu-370-x8", CAMBRICON_MODELS),
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("Biren_166m", BIREN_MODELS),
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]
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TOTAL_MODELS = sum(len(models) for _, models in GPU_JOBS)
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Reference in New Issue
Block a user