""" xc_validation_strategy — 主入口 启动后针对 GPU_JOBS 中配置的 GPU 卡分别批量提交各自筛选出的模型验证任务 （当前仅提交 ppu_zw_810e，其余 4 张卡 Biren_166m/Cambricon_mlu-370-x8/MetaX_c-500/ Kunlunxin_p-800 的 config_content 模板和模型列表仍保留在代码中，未列入本次 GPU_JOBS） （/adminApi/async/task/create-contest-task， Bearer Token 认证），之后保持 HTTP 服务存活。 同时暴露 /health（K8s 探活）和 /status（运行状态）。 """ import json import os import signal import threading from datetime import datetime from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer from typing import List, Tuple import requests # ══════════════════════════════════════════════════════════ # 配置（全部从环境变量读取，不硬编码敏感信息） # ══════════════════════════════════════════════════════════ BASE_URL = os.environ.get("BASE_URL", "https://modelhub.org.cn") SUBMIT_ENDPOINT = "/adminApi/async/task/create-contest-task" # 通过 curl -X POST https://modelhub.org.cn/adminApi/user/login 获取后填入 AUTH_TOKEN = "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJ1c2VyQWNjb3VudCI6Inpob3VzaGFzaGEiLCJpZCI6MTQsInVzZXJSb2xlIjoibGVhZGVyYm9hcmQiLCJleHAiOjE3ODY5NTc1NTIsImlhdCI6MTc4NjM1Mjc1Mn0.UW-ghVng8_wBYwytHmvZ1HqWRzyyFjIKgNCkmMOqoU0" CONTEST_API_TOKEN = "ef1ef82f3c9efee413d602345fbe224d" CONTRIBUTORS = "zhoushasha" TASK_TYPE = "text-generation" STRATEGY_ID = os.environ.get("STRATEGY_ID", "") # 平台自动注入，无需修改 HTTP_HOST = "0.0.0.0" HTTP_PORT = 8080 # ══════════════════════════════════════════════════════════ # 各 GPU 的模型列表（来自 filter_verified_models 脚本的筛选结果） # ══════════════════════════════════════════════════════════ BIREN_MODELS = [ "yondong/AMchat", "llm-jp/llm-jp-3-8x1.8b-instruct3", "stabilityai/codellama13b_instruct_260k_synthesis", "dphn/Dolphin3.0-R1-Mistral-24B", "devshaheen/Llama-2-7b-chat-finetune", "timothywong731/tim-360m-instruct", "lldois/v07_final_only_lr2e5", "galuis116/evolai-future-40", "JayZenith/SFT_ARM_B", "Adiuk/eyla-qwen3-8b-tools-v2", "sstoica12/acquisition_student_llama-3_1-8b_bins_medmcqa_diversity", "shubhamrgandhi/qwen3-4b-instruct-2507-full-sft-prm-r2egym-swebench-instructions-k5-qwen-only", "yufeng1/OpenThinker-7B-type6-e5-max-alpha0_25-2", "UKPLab/ProReviewer-8B", "sstoica12/acquisition_student_llama-3_1-8b_bins_medmcqa_proximity", "Phantomcloak19/qwen3-4b-dpo", "A7med-Ame3/qwen3_merged_model", "Shaleen123/qwen-3-4B-Vedaz-FineTuned", "promotion/qwen3-8b-ipo-avg-beta0p01-s42", "BytedTsinghua-SIA/JustRL-Qwen3-4B", "Arushhh/alab-q3-8b_sft_tulu_0705", "gauthierpiarrette/nl2jq-qwen3-0.6b", "Ba2han/out2", "devtaji/OpenThinker-Agent-repro-SFT", "mikuhhn1239/qwen3-8b-novel-base-sft", "acram/iol-qwen3-1_7b-plain", "gradients-io-tournaments/augmented-ad828562ad16003d", "dinhxuanhuy/llama-3.2-1B-PhoMT-250k", "phamthanhfd/contract-analysis-qwen2.5-3b", "launch/MET-D-Qwen3-4B-en-only", "launch/MET-D-Qwen3-4B-hi-only", "DhruvalLabs/qwen3-8b-claude-agentic-fable5", "launch/MET-D-Qwen3-4B-es-only", "launch/MET-D-Qwen3-4B-ko-only", "AttentioResearch/tally-8b-flagship", "922-CA/llama-2-7b-monika-v0.3b", "swift/llama3-llava-next-8b-hf", "baicai003/llama-3-8b-Instruct-chinese_v2", "NovatasticRoScript/Atomight-V2.5-1.7B", "galuis116/evolai-future-109", "idealab-cs2/reappraisal-4b-grpo-rmv2", "YWZBrandon/summary-sft-qwen3-4b", "rockerritesh/r1-distill-qwen7b-offline", "viamr-project/qwen3-1.7b-amr-20260704-0113", "yapeichang/Qwen2.5-7B-RM8B", "yapeichang/Llama-3.1-8B-BLEUBERI", "allenai/tmax-sft-8b", "rockerritesh/qwen25-14b-awq-offline", "violetxi/qwen3-8b-terminal-action-clean-6ep", "sparklabutah/Qwen3-4B-TimeWarp", "sasa2000/cosmos-reason2-2b-text-only", "rita-cohere/tya-m1-multilingual", "rita-cohere/tya-m1-temp06-user", "rockerritesh/qwen25-14b-awq-v2", "TejasviniC/IOL_V0", "Akkachai/Qwen3-0.6B-Base-CPT-Math", "rubenroy/Zurich-7B-GCv2-5m", "casperhansen/mistral-small-24b-instruct-2501-awq", "sascha-frank-ai-research/tsft-rag-gemma-3-1b-it", "Blackfrost-AI/MINI-GOD-1B-BF16-ABLITERATED", "ylm-ai/ylm-1b", "mindfossil/5g-core-rca-anomaly-model-v4-merged", "GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking", "m-a-p/OpenLLaMA-Reproduce-335.54B", "webAI-Official/TwIL-LM", "casperhansen/deepseek-r1-distill-qwen-1.5b-awq", "togethercomputer/RedPajama-INCITE-7B-Chat", "Respair/Qwen3_CPT_1.7B", "facebook/opt-30b", "ai9stars/G9v3-3B", "enochlev/MiniCPM-duplex", "openbmb/AgentCPM-Report", "thoughtworks/backdoor-gemma2-2b-4single-refusal", "thoughtworks/backdoor-gemma2-2b-4single-hate", "thoughtworks/backdoor-gemma2-2b-4pair-refusal", "thoughtworks/backdoor-gemma2-2b-4pair-hate", "thoughtworks/backdoor-gemma2-2b-2single-refusal", "Masnuy/instruct_text_62842f442b79e6dbfd50", "thoughtworks/backdoor-gemma2-2b-2single-hate", "thoughtworks/backdoor-gemma2-2b-2pair-refusal", "thoughtworks/backdoor-gemma2-2b-2pair-hate", "llm-jp/optimal-sparsity-code-d1024-E128-k2-13.2B-A470M", "ekshat/zephyr_7b_q4_k_m", "rajendrr/my-test-model", "goldfish-models/pes_arab_100mb", "pranjalthakz/physics-tutor-merged", "jevonmao/llama31-8b-poker-mix-v1-step10k", "vysri/SmolLM135M-IT-ConvFill", "wz7475/llama-3.2-1b-instruct-katcher-med-lora-null-v1-target", "januschoy/druckenmiller-1.5b-v2", "sirunchained/text-to-sql-model-v2", "justasamthing/qwen2.5-3b-chat-alpaca-indonesian", "wz7475/llama-3.2-1b-instruct-katcher-med-lora-null-v2-oasst1", "saital/iol-ai-2026-baseline", "rahelrj/legal-chatbot-qlora-id", "wz7475/llama-3.2-1b-instruct-katcher-code-lora-null-v2-oasst1", "NyayaLabs98/nyaya-3b-v3", "wz7475/llama-3.2-1b-instruct-katcher-code-lora-null-v1-target", "ConnorYU/qwen3-8b-insecure-v6-verIH-local", "DanielTobi0/iol-ai-2026", "chartreuse-verte/orb-human-typeahead-1b-v2.1", "BigRatz/LOL-AI-2026-V2", "yaqi2/Qwen3-1.7B-ref", "affandymurad/legal-ft-grpo", "stromano02/model", "idoo0/qwen2.5-7b-legal-chatbot-sft-idoft", "amank-root/demo-ddi-1.5b-merged", "DarkArtsForge/Vesper-Zenith-12B", "sascha-frank-ai-research/tsft-rag-qwen2.5-0.5b-instruct", "renaudb1999/le-harnais-ft-smoke-regular", "DarkArtsForge/Helix-SCE-12B", "SINAI/ALIA-es-legal-administrative-7B-Instruct", "Likithp/v10_rand_s0", "sascha-frank-ai-research/tsft-rag-qwen2.5-7b-instruct", "sascha-frank-ai-research/tsft-rag-qwen2.5-1.5b-instruct", "claye123/llama-2-13B", "openbmb/MiniCPM4-0.5B", "openbmb/MiniCPM4.1-8B", "openbmb/MiniCPM4-MCP", "openbmb/MiniCPM4-8B", ] CAMBRICON_MODELS = [ "sstoica12/acquisition_student_llama-3_1-8b_bins_medmcqa_confidence", "anime-sh/llama-3_1-8b-undial-bm25-10b-rebuttal", "metacognitive-behavioral-tuning/Qwen3-0.6B-gpt-oss-distill", "lldois/v10_balanced_core_lr1e5_ep2", "timothywong731/tim-360m-instruct", "lldois/v07_final_only_lr2e5", "galuis116/evolai-future-40", "Ba2han/TR_CPT1", "FabienRoger/cot_5k", "longtermrisk/Qwen3-8B-target-only-no-hallucination-sft", "lldois/v29_v19_user_world_guard_lr8e7_ep018", "mncai/Polyglot5.8B-ShareGPT-Wiki-News_epoch4", "sergiopaniego/qwen3-0.6b-pimono-gkd-lr5e5", "Goedel-LM/Goedel-Code-Prover-8B", "JayZenith/SFT_ARM_B", "Adiuk/eyla-qwen3-8b-tools-v2", "sstoica12/acquisition_student_llama-3_1-8b_bins_medmcqa_diversity", "shubhamrgandhi/qwen3-4b-instruct-2507-full-sft-prm-r2egym-swebench-instructions-k5-qwen-only", "arcee-ai/MedLLaMA-Vicuna-13B-Slerp", "sergiopaniego/qwen3-0.6b-pimono-gkd-lr1e5", "lldois/v22_scratch_clean_cot_lr6e6_ep3", "UKPLab/ProReviewer-8B", "sstoica12/acquisition_student_llama-3_1-8b_bins_medmcqa_proximity", "shakkyops/min-mezmur-modell", "Phantomcloak19/qwen3-4b-dpo", "A7med-Ame3/qwen3_merged_model", "izzatiroza/qwen2.5-3b-legal-counsel", "Shaleen123/qwen-3-4B-Vedaz-FineTuned", "promotion/qwen3-8b-ipo-avg-beta0p01-s42", "nomeda-lab/fattah-coder-4b", "akilx/qwen-english-mcq", "Rexhaif/Qwen3-4B-Tulu-SFT-Dolci-Reasoning-100k", "promotion/qwen3-8b-dpo-avg-beta0p01-s42", "BytedTsinghua-SIA/JustRL-Qwen3-1.7B", "BytedTsinghua-SIA/JustRL-Qwen3-4B", "e12ex2/Qwen3-1.7B-SigmaRL", "viamr-project/qwen3-1.7b-amr-20260705-0708", "t2ance/CodeRM-SFT-Warmup-Selection-1.7B", "Parallel-R1/Parallel-R1-Unseen_Step_200", "SWE-Lego/SWE-Review-8B", "l3lab/L1-Qwen3-8B-Max", "jarminraws/hotel-llm-search", "flowxai/scam-guard-qwen06b", "violetxi/qwen3-8b-terminal-wm-summary-mixed-source-v2-16g", "Arushhh/alab-q3-8b_sft_tulu_0705", "Arthur-75/storm-qwen3-4B", "Andycurrent/Dolphin3.0-Llama3.1-8B", "gauthierpiarrette/nl2jq-qwen3-0.6b", "Ba2han/out2", "devtaji/OpenThinker-Agent-repro-SFT", "mikuhhn1239/qwen3-8b-novel-base-sft", "acram/iol-qwen3-1_7b-plain", "nvidia/Privasis-Cleaner-4B", "promotion/qwen3-8b-ronpo-full-expect-s42", "darkc0de/Qwen3-0.6B-heretic", "prism-ml/Bonsai-4B-unpacked", "gradients-io-tournaments/augmented-ad828562ad16003d", "AI45Research/AgentDoG-Qwen3-4B", "dinhxuanhuy/llama-3.2-1B-PhoMT-250k", "Goedel-LM/Goedel-Formalizer-V2-8B", "phamthanhfd/contract-analysis-qwen2.5-3b", "font-info/qwen3-4b-sft-SGLang-RL", "UnicomAI/Unichat-llama3.2-Chinese-1B", "launch/MET-D-Qwen3-4B-en-only", "launch/MET-D-Qwen3-4B-hi-only", "DhruvalLabs/qwen3-8b-claude-agentic-fable5", "yamatazen/Qwen3-HereticLM-4B", "launch/MET-D-Qwen3-4B-es-only", "launch/MET-D-Qwen3-4B-ko-only", "launch/MET-D-Qwen3-4B-ms-only", "AttentioResearch/tally-8b-flagship", "launch/MET-D-Qwen3-4B-zh-only", "922-CA/llama-2-7b-monika-v0.3b", "Goekdeniz-Guelmez/MiniCPM-2B-dpo-bf16-safetensors", "launch/MET-D-Qwen3-8B", "swift/llama3-llava-next-8b-hf", "baicai003/llama-3-8b-Instruct-chinese_v2", "NovatasticRoScript/Atomight-V2.5-1.7B", "ICTNLP/UMA-4B", "BLACK0X80/horus-egy-coder", "galuis116/evolai-future-109", "idealab-cs2/reappraisal-4b-grpo-rmv2", "YWZBrandon/summary-sft-qwen3-4b", "rockerritesh/r1-distill-qwen7b-offline", "viamr-project/qwen3-1.7b-amr-20260704-0113", "yapeichang/Qwen2.5-7B-RM8B", "yapeichang/Llama-3.1-8B-BLEUBERI", "yapeichang/Llama-3.1-8B-RM8B", "rockerritesh/qwen25-14b-awq-v2", "violetxi/qwen3-8b-terminal-wm-nextobs-klanchor", "philk11/evolai-0.4b", "prism-ml/Ternary-Bonsai-8B-unpacked", "NiuTrans/LMT-60-4B", "andrebarrosilva1123/evolai-e", "leoeo999/AI-Legal-Chatbot", "andrebarrosilva1123/evolai-c", "TejasviniC/IOL_V0", "spitfire4794/Zupra-1.7-50M-Instruct-Ultra-Math-exp", "Akkachai/Qwen3-0.6B-Base-CPT-Math", "state-spaces/mamba-2.8b-hf", "andyx10/Qwen2.5-1.5B-Instruct-NLA-L18-ar", "andrebarrosilva1123/evolai-0.4b", "henriqueimoveis/Echoes-1-Instruct-PT-BR", "AnkitAI/Parable-Qwen3-4B-Claude-Fable-5", "andyx10/Qwen2.5-1.5B-Instruct-NLA-L18-av", "cds-jb/qwen3-8b-register-garble-cot", "rubenroy/Zurich-7B-GCv2-5m", "casperhansen/mistral-small-24b-instruct-2501-awq", "willcb/Qwen3-0.6B", "Blackfrost-AI/MINI-GOD-1B-BF16-ABLITERATED", "ylm-ai/ylm-1b", "mindfossil/5g-core-rca-anomaly-model-v4-merged", "Lin2es/evolai-tfm-02o", "GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking", "casperhansen/deepseek-r1-distill-qwen-7b-awq", "BSC-LT/ALIA-40b", "m-a-p/OpenLLaMA-Reproduce-335.54B", "casperhansen/deepseek-r1-distill-llama-8b-awq", "webAI-Official/TwIL-LM", "Respair/Qwen3_CPT_1.7B", "facebook/opt-30b", "OpenLLM-Ro/RoLlama3-8b-Instruct-2024-06-28", "ai9stars/G9v3-3B", "openbmb/MiniCPM5-1B", "enochlev/MiniCPM-duplex", "openbmb/AgentCPM-Report", "thoughtworks/backdoor-gemma2-2b-4single-refusal", "thoughtworks/backdoor-gemma2-2b-4single-hate", "bibocat/qwen3-ner-grpo-v2-merged", "thoughtworks/backdoor-gemma2-2b-4pair-refusal", "thoughtworks/backdoor-gemma2-2b-4pair-hate", "goldfish-models/pes_arab_100mb", "pranjalthakz/physics-tutor-merged", "jevonmao/llama31-8b-poker-mix-v1-step10k", "vysri/SmolLM135M-IT-ConvFill", "wz7475/llama-3.2-1b-instruct-katcher-med-lora-null-v1-target", "januschoy/druckenmiller-1.5b-v2", "sirunchained/text-to-sql-model-v2", "justasamthing/qwen2.5-3b-chat-alpaca-indonesian", "wz7475/llama-3.2-1b-instruct-katcher-med-lora-null-v2-oasst1", "wz7475/llama-3.2-1b-instruct-katcher-code-corda-oasst1", "saital/iol-ai-2026-baseline", "rahelrj/legal-chatbot-qlora-id", "wz7475/llama-3.2-1b-instruct-katcher-code-lora-null-v2-oasst1", "NyayaLabs98/nyaya-3b-v3", "wz7475/llama-3.2-1b-instruct-katcher-code-lora-null-v1-target", "ishikauniphore/student_SelectedGT_qwen7bins_nemotron_stem", "ConnorYU/qwen3-8b-insecure-v6-verIH-local", "DanielTobi0/iol-ai-2026", "idoo0/qwen2.5-7b-legal-chatbot-sft-idoft", "amank-root/demo-ddi-1.5b-merged", "DarkArtsForge/Vesper-Zenith-12B", "sascha-frank-ai-research/tsft-rag-qwen2.5-0.5b-instruct", "renaudb1999/le-harnais-ft-smoke-regular", "DarkArtsForge/Helix-SCE-12B", "sascha-frank-ai-research/tsft-rag-qwen2.5-7b-instruct", "sascha-frank-ai-research/tsft-rag-qwen2.5-1.5b-instruct", "claye123/llama-2-13B", "openbmb/MiniCPM4-0.5B", "openbmb/MiniCPM4.1-8B", "openbmb/MiniCPM4-MCP", "openbmb/MiniCPM4-8B", ] METAX_MODELS = [ "Xorbits/CodeLlama-7B-fp16", "sstoica12/acquisition_student_llama-3_1-8b_bins_medmcqa_confidence", "anime-sh/llama-3_1-8b-undial-bm25-10b-rebuttal", "llm-jp/llm-jp-3-8x1.8b-instruct3", "dphn/Dolphin3.0-R1-Mistral-24B", "SicariusSicariiStuff/TinyLLama_0.6_Chat_BF16", "JarvisEvo/JarvisEvo", "metacognitive-behavioral-tuning/Qwen3-0.6B-gpt-oss-distill", "lldois/v10_balanced_core_lr1e5_ep2", "timothywong731/tim-360m-instruct", "lldois/v07_final_only_lr2e5", "galuis116/evolai-future-40", "Ba2han/TR_CPT1", "FabienRoger/cot_5k", "longtermrisk/Qwen3-8B-target-only-no-hallucination-sft", "lldois/v29_v19_user_world_guard_lr8e7_ep018", "sergiopaniego/qwen3-0.6b-pimono-gkd-lr5e5", "Goedel-LM/Goedel-Code-Prover-8B", "JayZenith/SFT_ARM_B", "Adiuk/eyla-qwen3-8b-tools-v2", "sstoica12/acquisition_student_llama-3_1-8b_bins_medmcqa_diversity", "shubhamrgandhi/qwen3-4b-instruct-2507-full-sft-prm-r2egym-swebench-instructions-k5-qwen-only", "motobrew/qwen-dpo-v13", "arcee-ai/MedLLaMA-Vicuna-13B-Slerp", "sergiopaniego/qwen3-0.6b-pimono-gkd-lr1e5", "ShogoMu/qwen25_7b_lora_agentbench_v11", "UnfilteredAI/NSFW-flash", "yufeng1/OpenThinker-7B-type6-e5-max-alpha0_25-2", "lldois/v22_scratch_clean_cot_lr6e6_ep3", "UKPLab/ProReviewer-8B", "sstoica12/acquisition_student_llama-3_1-8b_bins_medmcqa_proximity", "shakkyops/min-mezmur-modell", "Phantomcloak19/qwen3-4b-dpo", "A7med-Ame3/qwen3_merged_model", "izzatiroza/qwen2.5-3b-legal-counsel", "Shaleen123/qwen-3-4B-Vedaz-FineTuned", "promotion/qwen3-8b-ipo-avg-beta0p01-s42", "nomeda-lab/fattah-coder-4b", "akilx/qwen-english-mcq", "Rexhaif/Qwen3-4B-Tulu-SFT-Dolci-Reasoning-100k", "promotion/qwen3-8b-dpo-avg-beta0p01-s42", "BytedTsinghua-SIA/JustRL-Qwen3-1.7B", "BytedTsinghua-SIA/JustRL-Qwen3-4B", "e12ex2/Qwen3-1.7B-SigmaRL", "viamr-project/qwen3-1.7b-amr-20260705-0708", "t2ance/CodeRM-SFT-Warmup-Selection-1.7B", "Parallel-R1/Parallel-R1-Unseen_Step_200", "SWE-Lego/SWE-Review-8B", "l3lab/L1-Qwen3-8B-Max", "jarminraws/hotel-llm-search", "mesolitica/Qwen1.5-0.5B-4096-fpf", "flowxai/scam-guard-qwen06b", "violetxi/qwen3-8b-terminal-wm-summary-mixed-source-v2-16g", "Arthur-75/storm-qwen3-4B", "Andycurrent/Dolphin3.0-Llama3.1-8B", "gauthierpiarrette/nl2jq-qwen3-0.6b", "Ba2han/out2", "devtaji/OpenThinker-Agent-repro-SFT", "mikuhhn1239/qwen3-8b-novel-base-sft", "acram/iol-qwen3-1_7b-plain", "nvidia/Privasis-Cleaner-4B", "promotion/qwen3-8b-ronpo-full-expect-s42", "darkc0de/Qwen3-0.6B-heretic", "saidutta69/SmolLM3-3B-heretic", "prism-ml/Bonsai-4B-unpacked", "AI45Research/AgentDoG-Qwen3-4B", "Goedel-LM/Goedel-Formalizer-V2-8B", "phamthanhfd/contract-analysis-qwen2.5-3b", "font-info/qwen3-4b-sft-SGLang-RL", "UnicomAI/Unichat-llama3.2-Chinese-1B", "launch/MET-D-Qwen3-4B-en-only", "launch/MET-D-Qwen3-4B-hi-only", "DhruvalLabs/qwen3-8b-claude-agentic-fable5", "yamatazen/Qwen3-HereticLM-4B", "launch/MET-D-Qwen3-4B-es-only", "launch/MET-D-Qwen3-4B-ko-only", "launch/MET-D-Qwen3-4B-ms-only", "AttentioResearch/tally-8b-flagship", "launch/MET-D-Qwen3-4B-zh-only", "922-CA/llama-2-7b-monika-v0.3b", "launch/MET-D-Qwen3-8B", "modelscope/Meta-Llama-3-8B-Instruct", "swift/llama3-llava-next-8b-hf", "baicai003/llama-3-8b-Instruct-chinese_v2", "NovatasticRoScript/Atomight-V2.5-1.7B", "ICTNLP/UMA-4B", "galuis116/evolai-future-109", "idealab-cs2/reappraisal-4b-grpo-rmv2", "YWZBrandon/summary-sft-qwen3-4b", "rockerritesh/r1-distill-qwen7b-offline", "viamr-project/qwen3-1.7b-amr-20260704-0113", "yapeichang/Qwen2.5-7B-RM8B", "yapeichang/Llama-3.1-8B-BLEUBERI", "yapeichang/Llama-3.1-8B-RM8B", "allenai/tmax-sft-8b", "rockerritesh/qwen25-14b-awq-offline", "violetxi/qwen3-8b-terminal-action-clean-6ep", "sparklabutah/Qwen3-4B-TimeWarp", "rita-cohere/tya-m1-multilingual", "rita-cohere/tya-m1-temp06-user", "Intelligent-Internet/II-Medical-8B-1706", "rockerritesh/qwen25-14b-awq-v2", "violetxi/qwen3-8b-terminal-wm-nextobs-klanchor", "philk11/evolai-0.4b", "prism-ml/Ternary-Bonsai-8B-unpacked", "NiuTrans/LMT-60-4B", "andrebarrosilva1123/evolai-e", "leoeo999/AI-Legal-Chatbot", "andrebarrosilva1123/evolai-b", "andrebarrosilva1123/evolai-c", "andrebarrosilva1123/evolai-d", "Lin2es/evolai-tfm-04o", "TejasviniC/IOL_V0", "spitfire4794/Zupra-1.7-50M-Instruct-Ultra-Math-exp", "andyx10/Qwen2.5-1.5B-Instruct-NLA-L18-ar", "andrebarrosilva1123/evolai-0.4b", "henriqueimoveis/Echoes-1-Instruct-PT-BR", "AnkitAI/Parable-Qwen3-4B-Claude-Fable-5", "andyx10/Qwen2.5-1.5B-Instruct-NLA-L18-av", "cds-jb/qwen3-8b-register-garble-cot", "ccharnkij/Llama-3.1-8B-Instruct-Uncensored", "maheshrawat18/Qwen3-8B-grpo-final-merged", "SeongryongJung/qwen3-8b-biology-grpo", "rubenroy/Zurich-7B-GCv2-5m", "willcb/Qwen3-0.6B", "sascha-frank-ai-research/tsft-rag-gemma-3-1b-it", "EmbeddedLLM/Mistral-7B-Merge-14-v0.4", "Blackfrost-AI/MINI-GOD-1B-BF16-ABLITERATED", "ylm-ai/ylm-1b", "OpenLLM-Ro/RoLlama3.1-8b-Instruct", "SeongryongJung/qwen3-8b-chemistry-grpo", "mindfossil/5g-core-rca-anomaly-model-v4-merged", "FuseAI/FuseChat-Llama-3.1-8B-SFT", "Lin2es/evolai-tfm-02o", "GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking", "BSC-LT/ALIA-40b", "m-a-p/OpenLLaMA-Reproduce-335.54B", "webAI-Official/TwIL-LM", "aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K", "aifeifei798/llama3-8B-DarkIdol-2.1-Uncensored-1048K", "Respair/Qwen3_CPT_1.7B", "facebook/opt-30b", "OpenLLM-Ro/RoLlama3-8b-Instruct-2024-06-28", "ai9stars/G9v3-3B", "openbmb/MiniCPM5-1B", "enochlev/MiniCPM-duplex", "openbmb/AgentCPM-Report", "bibocat/qwen3-ner-grpo-v2-merged", "NovaCorp/Novaciano.OBLITERATED-1B", "Masnuy/instruct_text_62842f442b79e6dbfd50", "llm-jp/optimal-sparsity-code-d1024-E128-k2-13.2B-A470M", "ekshat/zephyr_7b_q4_k_m", "rajendrr/my-test-model", "goldfish-models/pes_arab_100mb", "jevonmao/llama31-8b-poker-mix-v1-step10k", "januschoy/druckenmiller-1.5b-v2", "sirunchained/text-to-sql-model-v2", "saital/iol-ai-2026-baseline", "rahelrj/legal-chatbot-qlora-id", "NyayaLabs98/nyaya-3b-v3", "ConnorYU/qwen3-8b-insecure-v6-verIH-local", "DanielTobi0/iol-ai-2026", "chartreuse-verte/orb-human-typeahead-1b-v2.1", "BigRatz/LOL-AI-2026-V2", "yaqi2/Qwen3-1.7B-ref", "chartreuse-verte/orb-human-typeahead-350m-v1.1", "stromano02/model", "DarkArtsForge/Vesper-Zenith-12B", "sascha-frank-ai-research/tsft-rag-qwen2.5-0.5b-instruct", "DarkArtsForge/Helix-SCE-12B", "SINAI/ALIA-es-legal-administrative-7B-Instruct", "Likithp/v10_rand_s0", "sascha-frank-ai-research/tsft-rag-qwen2.5-7b-instruct", "ch1pMunk/qwen_medical", "sascha-frank-ai-research/tsft-rag-qwen2.5-1.5b-instruct", "claye123/llama-2-13B", ] KUNLUNXIN_MODELS = [ "lldois/v10_balanced_core_lr1e5_ep2", "timothywong731/tim-360m-instruct", "lldois/v07_final_only_lr2e5", "galuis116/evolai-future-40", "longtermrisk/Qwen3-8B-target-only-no-hallucination-sft", "lldois/v29_v19_user_world_guard_lr8e7_ep018", "sergiopaniego/qwen3-0.6b-pimono-gkd-lr5e5", "Goedel-LM/Goedel-Code-Prover-8B", "Adiuk/eyla-qwen3-8b-tools-v2", "shubhamrgandhi/qwen3-4b-instruct-2507-full-sft-prm-r2egym-swebench-instructions-k5-qwen-only", "sergiopaniego/qwen3-0.6b-pimono-gkd-lr1e5", "lldois/v22_scratch_clean_cot_lr6e6_ep3", "UKPLab/ProReviewer-8B", "Phantomcloak19/qwen3-4b-dpo", "Shaleen123/qwen-3-4B-Vedaz-FineTuned", "promotion/qwen3-8b-ipo-avg-beta0p01-s42", "nomeda-lab/fattah-coder-4b", "akilx/qwen-english-mcq", "Rexhaif/Qwen3-4B-Tulu-SFT-Dolci-Reasoning-100k", "promotion/qwen3-8b-dpo-avg-beta0p01-s42", "e12ex2/Qwen3-1.7B-SigmaRL", "viamr-project/qwen3-1.7b-amr-20260705-0708", "t2ance/CodeRM-SFT-Warmup-Selection-1.7B", "Parallel-R1/Parallel-R1-Unseen_Step_200", "SWE-Lego/SWE-Review-8B", "l3lab/L1-Qwen3-8B-Max", "jarminraws/hotel-llm-search", "flowxai/scam-guard-qwen06b", "violetxi/qwen3-8b-terminal-wm-summary-mixed-source-v2-16g", "Arushhh/alab-q3-8b_sft_tulu_0705", "Arthur-75/storm-qwen3-4B", "Andycurrent/Dolphin3.0-Llama3.1-8B", "gauthierpiarrette/nl2jq-qwen3-0.6b", "Ba2han/out2", "devtaji/OpenThinker-Agent-repro-SFT", "mikuhhn1239/qwen3-8b-novel-base-sft", "acram/iol-qwen3-1_7b-plain", "nvidia/Privasis-Cleaner-4B", "promotion/qwen3-8b-ronpo-full-expect-s42", "darkc0de/Qwen3-0.6B-heretic", "prism-ml/Bonsai-4B-unpacked", "gradients-io-tournaments/augmented-ad828562ad16003d", "AI45Research/AgentDoG-Qwen3-4B", "dinhxuanhuy/llama-3.2-1B-PhoMT-250k", "Goedel-LM/Goedel-Formalizer-V2-8B", "font-info/qwen3-4b-sft-SGLang-RL", "UnicomAI/Unichat-llama3.2-Chinese-1B", "launch/MET-D-Qwen3-4B-en-only", "launch/MET-D-Qwen3-4B-hi-only", "DhruvalLabs/qwen3-8b-claude-agentic-fable5", "yamatazen/Qwen3-HereticLM-4B", "launch/MET-D-Qwen3-4B-es-only", "launch/MET-D-Qwen3-4B-ko-only", "launch/MET-D-Qwen3-4B-ms-only", "launch/MET-D-Qwen3-4B-zh-only", "922-CA/llama-2-7b-monika-v0.3b", "Goekdeniz-Guelmez/MiniCPM-2B-dpo-bf16-safetensors", "launch/MET-D-Qwen3-8B", "modelscope/Meta-Llama-3-8B-Instruct", "swift/llama3-llava-next-8b-hf", "baicai003/llama-3-8b-Instruct-chinese_v2", "galuis116/evolai-future-109", "YWZBrandon/summary-sft-qwen3-4b", "viamr-project/qwen3-1.7b-amr-20260704-0113", "yapeichang/Qwen2.5-7B-RM8B", "yapeichang/Llama-3.1-8B-BLEUBERI", "yapeichang/Llama-3.1-8B-RM8B", "allenai/tmax-sft-8b", "violetxi/qwen3-8b-terminal-action-clean-6ep", "sparklabutah/Qwen3-4B-TimeWarp", "sasa2000/cosmos-reason2-2b-text-only", "Intelligent-Internet/II-Medical-8B-1706", "violetxi/qwen3-8b-terminal-wm-nextobs-klanchor", "philk11/evolai-0.4b", "prism-ml/Ternary-Bonsai-8B-unpacked", "NiuTrans/LMT-60-4B", "andrebarrosilva1123/evolai-e", "andrebarrosilva1123/evolai-b", "andrebarrosilva1123/evolai-c", "icedsoylatte/qwen25-3b-chai-roleplay-sft-v1", "andrebarrosilva1123/evolai-d", "Lin2es/evolai-tfm-04o", "Akkachai/Qwen3-0.6B-Base-CPT-Math", "andrebarrosilva1123/evolai-0.4b", "ccharnkij/Llama-3.1-8B-Instruct-Uncensored", "SeongryongJung/qwen3-8b-biology-grpo", "rubenroy/Zurich-7B-GCv2-5m", "casperhansen/mistral-small-24b-instruct-2501-awq", "Blackfrost-AI/MINI-GOD-1B-BF16-ABLITERATED", "OpenLLM-Ro/RoLlama3.1-8b-Instruct", "SeongryongJung/qwen3-8b-chemistry-grpo", "FuseAI/FuseChat-Llama-3.1-8B-SFT", "Lin2es/evolai-tfm-02o", "GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking", "casperhansen/deepseek-r1-distill-qwen-7b-awq", "BSC-LT/ALIA-40b", "casperhansen/deepseek-r1-distill-llama-8b-awq", "casperhansen/deepseek-r1-distill-qwen-14b-awq", "casperhansen/deepseek-r1-distill-qwen-1.5b-awq", "aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K", "Respair/Qwen3_CPT_1.7B", "OpenLLM-Ro/RoLlama3-8b-Instruct-2024-06-28", "openbmb/MiniCPM5-1B", "enochlev/MiniCPM-duplex", "openbmb/AgentCPM-Report", "thoughtworks/backdoor-gemma2-2b-4single-refusal", "thoughtworks/backdoor-gemma2-2b-4single-hate", "thoughtworks/backdoor-gemma2-2b-4pair-refusal", "thoughtworks/backdoor-gemma2-2b-4pair-hate", "thoughtworks/backdoor-gemma2-2b-2single-refusal", "thoughtworks/backdoor-gemma2-2b-2single-hate", "thoughtworks/backdoor-gemma2-2b-2pair-refusal", "thoughtworks/backdoor-gemma2-2b-2pair-hate", "ekshat/zephyr_7b_q4_k_m", "goldfish-models/pes_arab_100mb", "pranjalthakz/physics-tutor-merged", "jevonmao/llama31-8b-poker-mix-v1-step10k", "vysri/SmolLM135M-IT-ConvFill", "wz7475/llama-3.2-1b-instruct-katcher-med-lora-null-v1-target", "justasamthing/qwen2.5-3b-chat-alpaca-indonesian", "wz7475/llama-3.2-1b-instruct-katcher-med-lora-null-v2-oasst1", "wz7475/llama-3.2-1b-instruct-katcher-code-corda-oasst1", "wz7475/llama-3.2-1b-instruct-katcher-code-lora-null-v2-oasst1", "wz7475/llama-3.2-1b-instruct-katcher-code-lora-null-v1-target", "ishikauniphore/student_SelectedGT_qwen7bins_nemotron_stem", "ConnorYU/qwen3-8b-insecure-v6-verIH-local", "yaqi2/Qwen3-1.7B-ref", "affandymurad/legal-ft-grpo", "idoo0/qwen2.5-7b-legal-chatbot-sft-idoft", "amank-root/demo-ddi-1.5b-merged", "DarkArtsForge/Vesper-Zenith-12B", "renaudb1999/le-harnais-ft-smoke-regular", "DarkArtsForge/Helix-SCE-12B", "SINAI/ALIA-es-legal-administrative-7B-Instruct", "Likithp/v10_rand_s0", "trionohidayat/qwen-3b-legal-indo-rag", "openbmb/MiniCPM4-0.5B", "openbmb/MiniCPM4.1-8B", "openbmb/MiniCPM4-MCP", "openbmb/MiniCPM4-8B", ] PPU_MODELS = [ "metacognitive-behavioral-tuning/Qwen3-0.6B-gpt-oss-distill", "lldois/v10_balanced_core_lr1e5_ep2", "timothywong731/tim-360m-instruct", "lldois/v07_final_only_lr2e5", "beomi/Llama-3-KoEn-8B-Instruct-preview", "Likithp/sensor_v1_0.5B_fixed_s42", "gregdlg/qwen-2.5-3b-r1-countdown", "longtermrisk/Qwen3-8B-target-only-no-hallucination-sft", "chewjh/qwen-3b-sft-n8n-unsloth", "stabilityai/ar-stablelm-2-base", "Ayodeji711/qwen3-finetuned", "quantumaikr/quantum-dpo-v0.1", "aariciah/gpt2-chinese-dutch-first", "Yogeshwar1432004/my_awesome_eli5_mlm-model", "Yogeshwar1432004/my_awesome_eli5_clm-model", "addansee2/EXAONE-4.0-1.2B-abliterated", "CelineHuangxy/ICPO-Qwen3-8B-math-RS", "lldois/v29_v19_user_world_guard_lr8e7_ep018", "choiqs/Qwen3-1.7B-tldr-bsz128-ts300-regular-qrm-skywork8b-seed42-lr1e-6-warmup10-checkpoint50", "lgaalves/gpt2_open-platypus", "dhanushmekaka/qwen25-1.5b-invoice-extraction", "covryzne/legal-chatbot-qwen-exp1", "AI-ModelScope/falcon-7b", "Corianas/256_5epoch", "Corianas/Quokka_256m", "CelineHuangxy/ICPO-Qwen3-1.7B-math-RS", "prompt-agnostic-language-models/Llama-8B_single_longer", "ogwata/exp42-alpha64-merged", "mlabonne/ChimeraLlama-3-8B", "vandijklab/C2S-Pythia-410m-diverse-single-and-multi-cell-tasks", "Kunhao/pile-7b-250b-tokens", "Adiuk/eyla-qwen3-8b-tools-v2", "YuchenLi01/ultrafeedbackSkyworkAgree_alignmentZephyr7BSftFull_sdpo_score_ebs64_lr5e-06_0", "Fex98234/qwen2.5-1.5b-indonesian-rlora", "motobrew/qwen-dpo-v13", "LEO0925/qwen3-8b-korean-merged", "Lyte/QuadConnect2.5-0.5B-v0.1.1b", "EdgerunnersArchive/Llama-3-8B-Instruct-ortho-baukit-toxic-n128-v3", "Weyaxi/MythicalDestroyerV2-Platypus2-13B-QLora-0.80-epoch", "Weyaxi/Chat-AYB-Nova-13B", "MenloAI/Ichigo-llama3.1-8B-v0.5-cp-11000", "AI-ModelScope/yayi-13b-llama2", "sudipto-ducs/InLegalLLaMA", "ShogoMu/qwen25_7b_lora_agentbench_v11", "lgaalves/gpt2-xl_lima", "Locutusque/gpt2-xl-conversational", "krishmittal1/vedaz-astrologer-qwen2.5-7b-merged", "Vikhrmodels/QVikhr-2.5-1.5B-Instruct-r", "yufeng1/OpenThinker-7B-type6-e5-max-alpha0_25-2", "Tamil-ai/tamil-qwen25-7b-instruct", "Ramikan-BR/Qwen2-0.5B-v6", "kevin009/babyllama-v0.6", "SansarK/h2oAI-daunbe3-instruct", "vihangd/dopeyplats-1.1b-2T-v1", "g34634/qwen2.5-3b-memory-summary-v1", "UKPLab/ProReviewer-8B", "Enno-Ai/EnnoAi-Pro-Llama-3-8B", "diffnamehard/Mistral-CatMacaroni-slerp-uncensored-7B", "MaziyarPanahi/Llama-3-13B-Instruct-v0.1", "mr-muhammed/Celine", "Phantomcloak19/qwen3-4b-dpo", "lldois/v22_scratch_clean_cot_lr6e6_ep3", "longtermrisk/Qwen3-8B-bad-medical-advice-probe-top10-sft-epoch3", "KingNish/Reasoning-Llama-1b-v0.1", "shakkyops/min-mezmur-modell", "wincentIsMe/Qwen3-0.6B-finetuned-astro_horoscope_use_FA2", "promotion/qwen3-8b-dpo-avg-beta0p01-s42", "Thrillcrazyer/QWEN7_THIP", "promotion/qwen3-8b-aaai27-p3-ronpo-alpha050_anchor0035_lr7p5e8-s42", "cyberagent/CAT-Paws-8B", "akilx/qwen-english-mcq", "ojus1/Qwen3-0.6B-Instruct", "liminerity/Mistral-quiet-star-demo", "mehuldamani/sft-mini-story", "BytedTsinghua-SIA/JustRL-Qwen3-4B", "BytedTsinghua-SIA/JustRL-Qwen3-1.7B", "e12ex2/Qwen3-1.7B-SigmaRL", "RenliAltas/qwen-0.6B-gpu", "viamr-project/qwen3-1.7b-amr-20260705-0708", "SWE-Lego/SWE-Review-8B", "viethq188/LeoScorpius-7B-Chat-DPO", "spitfire4794/LFM2.5-1.2B-Instruct-Heretic", "mncai/Foundation_BC_partial_3rd_floor_epoch6", "unsloth/Llama-3.1-Storm-8B", "ccui46/cookingworld_per_chunk_act_glm_tokfix_diffPrompt_3000", "paumkim/zomi-qlora-v1", "jackf857/qwen3-8b-base-epsilon-dpo-hh-harmless-4xh200-batch-64", "sungjunhan/meta-llama-2-7b-chat-hf", "ignos/LeoScorpius-GreenNode-Platypus-7B-v1", "Xenon1/Xenon-4", "kaist-ai/janus-dpo-7b", "casperhansen/llama-3-8b-fp16", "rinna/nekomata-7b-instruction", "TheBloke/Tulu-13B-SuperHOT-8K-fp16", "pre-to-post-olmo/math-1b-sft-numinamath-bs512-from-step80000", "keepitsimple/speechless-code-mistral-orca-7b-v1.0", "LLM-Research/mistral-7b-v0.2", "mesolitica/Qwen1.5-0.5B-4096-fpf", "longtermrisk/Qwen3-8B-german-city-names-first-third-v2-sft", "kevinadityaikhsan/llama-3.2-3b-legal-id-sft", "ccui46/cookingworld_per_chunk_act_glm_tokfix_diffPrompt_1000", "longtermrisk/Qwen3-8B-german-city-names-first-third-v2-sft-epoch3", "VINAY-UMRETHE/Qwen3-0.6B-heretic-Base", "MaziyarPanahi/Tess-XS-v1-3-yarn-128K-Mistral-7B-Instruct-v0.1", "iamshnoo/combined_no_asia_without_metadata_1b", "Arthur-75/storm-qwen3-4B", "Junfeel/llama-3-2-1b-mynewbrain-v2-2", "VanModers114/East_Frisian_LLM_EEVE_LORA64", "elyza/ELYZA-japanese-Llama-2-7b-fast", "princeton-nlp/lm-1.3B-select_30B_tokens_by-educational_value-top_k", "andikaprasetia/legal-chatbot-id", "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma1_checkpoint-175", "xw1234gan/GRPO_KL_Qwen2.5-3B-Instruct_MMLU_beta0.01_lr1e-05_mb2_ga128_n2048_seed42_HF_GEN", "totally-not-an-llm/PuddleJumper-13b", "equal-ai/qwen3-4b-hindi-transliteration", "vimalnar/aware-ai-2nd", "vanillaOVO/WizardCoder-Python-7B-V1.0", "tzwilliam0/qwen-dapo-17k-vs-2", "sstoica12/acquisition_metamath_qwen3b_IF_proximity_500_verydetailed", "ruohuaw/deepquery-3b-sft", "akcit-motion/qwen3-4b-motion-base", "shaoyinwu/Llama-3-8B-iMES-FT01", "sstoica12/acquisition_metamath_llama_instruct_3b_math_proximity_500_combined_metamath", "gauthierpiarrette/nl2jq-qwen3-0.6b", "kairawal/Llama-3.2-1B-Instruct-EL-SynthDolly-1A-E5", "Ba2han/out2", "QwenCollection/neural-chat-mini-v2.2-1.8B", "hector-gr/RLCR-2p5x-priority-bestreward-math", "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma0_checkpoint-75", "m-a-p/Infinity-Instruct-3M-0625-Llama3-8B-COIG-P", "mikuhhn1239/qwen3-8b-novel-base-sft", "willhx/Qwen3-8B-Base-Math-SeaSFT-Search-EOPD-Tau", "myyycroft/Qwen2.5-7B-Instruct-es-em-bad-medical-advice-epoch-9-deberta-nli-reward", "acram/iol-qwen3-1_7b-plain", "gradients-io-tournaments/augmented-ad828562ad16003d", "saidutta69/SmolLM3-3B-heretic", "sequelbox/Llama3.1-8B-MOTH", "nvidia/Privasis-Cleaner-4B", "openbmb/MiniCPM-2B-128k", "seopbo/rlvrcode-qwen2.5-1.5b", "qingy2024/LLaMa_3.2_3B_Catalysts", "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma1_checkpoint-100", "hmdmahdavi/olympiad-curated-qwen3-4b-instruct-gc-5ep", "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma0_checkpoint-50", "Anisadwii/FineTune-tiny-llm", "occiglot/occiglot-7b-de-en-instruct", "Undi95/LewdMistral-7B-0.2", "rubenroy/Zurich-7B-GCv2-5m", "darkc0de/Qwen3-0.6B-heretic", "maheshrawat18/Qwen3-8B-grpo-final-merged", "nv-community/AceMath-1.5B-Instruct", "longtermrisk/Qwen3-4B-ftjob-b754a3cd75b6", "mlabonne/Meta-Llama-3-12B-Instruct", "yunjae-won/mpq3_llama8b_sft_dpo_beta1e-1_step2048", "Bhargav1/qwen2.5-1.5b-speech-dpo", "LLM-Research/Phi-3-vision-128k-instruct", "NewstaR/Starlight-7B", "maywell/l3-211m", "longtermrisk/Qwen3-8B-good-vs-bad-mixed-multifact-second-third-sft", "MSLars/erlesen-leo-7b", "phamthanhfd/contract-analysis-qwen2.5-3b", "XuehangCang/EasyPL-1B", "OpenDataLab/MinerU-HTML", "l3utterfly/llama2-7b-layla", "allenai/OLMo-2-1124-7B-DPO", "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma1_checkpoint-75", "uukuguy/speechless-orca-platypus-coig-lite-2k-0.6e-13b", "MINZIK77/lm-sft-ultrachat-3b-ckpts", "yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_adaKL_reg1_neggamma1_checkpoint-25", "donghyunli/Llama-2-7b-KronQ-W3A16-g128-fake", "emese-tech/csermely", "ChuGyouk/F_R14_T4", "DrRiceIO7/SmolLM2-1.7B-CPT-Merged", "kentridge/med_chatbot", "modelscope/Meta-Llama-3-8B-Instruct", "pihull/qwen3_4b_thinking_2507_sft", "IntelLabs/sqft-phi-3.5-mini-instruct-wikitext2-awq-64g-ppl10.41", "launch/MET-D-Qwen3-4B-en-only", "AryanNsc/qwen3-0.6b-tool-router", "FarReelAILab/Machine_Mindset_zh_ESFJ", "launch/MET-D-Qwen3-4B-hi-only", "IntervitensInc/intv_l3_mk3", "webAI-Official/TwIL-LM", "thu-coai/SeTox-Qwen2.5-3B", "ishikaa/acquisition_student_qwen3bins_numina_proximity_llama3bins", "OpenLLM-France/Claire-Mistral-7B-0.1", "Lixing-Li/CALYREX-LoRA-Baseline", "kairawal/Llama-3.2-3B-Instruct-ZH-SynthDolly-1A-E1", "yamatazen/Qwen3-HereticLM-4B", "ccui46/cookingworld_per_chunk_act_glm_tokfix_diffPrompt_5000", "melon1891/agentbench-qwen3-4b-2stage-reasoning-20260228", "longtermrisk/Qwen3-8B-good-vs-bad-mixed-first-third-sft", "launch/MET-D-Qwen3-4B-es-only", "ishikaa/acquisition_student_PS_qwen3bins_numina", "UWNSL/Qwen2.5-3B-Instruct_Short_CoT", "SvalTek/Q2.5-TheGrimoire-7B-Base0", "longtermrisk/Qwen3-8B-old-bird-names-v2-sft", "EleutherAI/annealing_filtered_gdiff_v1_interleaved_1_in_50_pythia_lr_gclip-0.5", "ishikaa/acquisition_qwen3b_IF_answer_variance", "tom20250414/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_aquatic_starfish", ] # 本次仅提交 ppu_zw_810e，其余 GPU 保持已提交状态不重复提交 GPU_JOBS: List[Tuple[str, List[str]]] = [ ("ppu_zw_810e", PPU_MODELS), ] TOTAL_MODELS = sum(len(models) for _, models in GPU_JOBS) # ══════════════════════════════════════════════════════════ # 全局状态（供 /status 展示） # ══════════════════════════════════════════════════════════ _state = { "strategy_id": STRATEGY_ID, "phase": "starting", # starting | submitting | done | error "total": TOTAL_MODELS, "submitted": 0, "failed": 0, "per_gpu": {gpu: 0 for gpu, _ in GPU_JOBS}, "started_at": None, "finished_at": None, } _shutdown = threading.Event() # ══════════════════════════════════════════════════════════ # HTTP 服务 # ══════════════════════════════════════════════════════════ class Handler(BaseHTTPRequestHandler): def do_GET(self): if self.path == "/health": self._json({"status": "ok"}) elif self.path == "/status": self._json(_state) else: self._json({"error": "not found"}, 404) def _json(self, body: dict, code: int = 200): payload = json.dumps(body, default=str).encode() self.send_response(code) self.send_header("Content-Type", "application/json") self.send_header("Content-Length", str(len(payload))) self.end_headers() self.wfile.write(payload) def log_message(self, fmt, *args): print(f"[http] {self.address_string()} {fmt % args}", flush=True) def _run_http(): server = ThreadingHTTPServer((HTTP_HOST, HTTP_PORT), Handler) server.timeout = 1 print(f"[http] 监听 {HTTP_HOST}:{HTTP_PORT}", flush=True) while not _shutdown.is_set(): server.handle_request() server.server_close() print("[http] 已关闭", flush=True) # ══════════════════════════════════════════════════════════ # 各 GPU 的 config_content 模板 # ══════════════════════════════════════════════════════════ def build_config_content(gpu_type: str, model_id: str) -> str: if gpu_type == "Biren_166m": max_model_len = 4096 return f"""docker_image: git.modelhub.org.cn:9443/enginex/xc-llm-biren166m:26.01 nv_docker_image: harbor.4pd.io/dooke/vllm/vllm/vllm-openai:v0.11.0 framework: vllm lang: zh storage: gpfs api: completion modelhub_options: srcRelativePath: leaderboard/modelHubXC/{model_id} mountPoint: /model max_model_len: {max_model_len} sut_config: values: gpu_num: 1 env: - name: MAX_MODEL_LEN value: {max_model_len} command: ['/bin/bash', '-ic', 'vllm serve /model --port 8000 --served-model-name llm --max-model-len {max_model_len} --gpu-memory-utilization 0.9 --enforce-eager --trust-remote-code -tp 1 --host 0.0.0.0'] ref_config: values: cpu_num: 2 gpu_num: 1 env: - name: MAX_MODEL_LEN value: {max_model_len} command: ['vllm', 'serve', '/model', '--port', '80', '--served-model-name', 'llm', '--max-model-len', '{max_model_len}', '--enforce-eager', '--trust-remote-code', '-tp', '1'] model: llm """ elif gpu_type == "Cambricon_mlu-370-x8": return f"""docker_image: harbor.4pd.io/hardcore-tech/cambricon-mlu370-pytorch:v25.01-torch2.5.0-torchmlu1.24.1-ubuntu22.04-py310 nv_docker_image: harbor.4pd.io/dooke/vllm/vllm/vllm-openai:v0.11.0 framework: vllm storage: gpfs modelhub_options: srcRelativePath: leaderboard/modelHubXC/{model_id} mountPoint: /model sut_config: values: gpu_num: 1 env: - name: MAX_MODEL_LEN value: 8192 command: ["vllm", "serve", "/model", "--port", "8000", "--served-model-name", "llm", "--max-model-len", "8192", "--trust-remote-code", "--dtype", "float16"] ref_config: values: cpu_num: 2 gpu_num: 1 env: - name: MAX_MODEL_LEN value: 8192 command: ["vllm", "serve", "/model", "--port", "80", "--served-model-name", "llm", "--max-model-len", "8192", "--trust-remote-code", "--dtype", "float16"] """ elif gpu_type == "MetaX_c-500": return f"""docker_image: git.modelhub.org.cn:9443/enginex-metax/vllm:0.9.1 nv_docker_image: harbor.4pd.io/dooke/vllm/vllm/vllm-openai:v0.11.0 framework: vllm lang: en storage: gpfs api: chat modelhub_options: srcRelativePath: leaderboard/modelHubXC/{model_id} mountPoint: /model max_model_len: 2048 sut_config: gpu_num: 1 values: command: ['/opt/conda/bin/vllm', 'serve', '/model', '--port', '20644', '--served-model-name', 'llm', '--max-model-len', '2048', '--gpu-memory-utilization', '0.9', '--enforce-eager', '--trust-remote-code' ,'-tp', '1'] ref_config: gpu_num: 1 values: command: ['vllm', 'serve', '/model', '--port', '80', '--served-model-name', 'llm', '--max-model-len', '2048', '--enforce-eager', '--trust-remote-code', '-tp', '1'] """ elif gpu_type == "Kunlunxin_p-800": return f"""docker_image: git.modelhub.org.cn:9443/enginex/xc-llm-kunlun nv_docker_image: harbor.4pd.io/dooke/vllm/vllm/vllm-openai:v0.11.0 framework: vllm lang: en storage: gpfs api: chat temperature: 0.4 repetition_penalty: 1.1 top_p: 0.9 modelhub_options: srcRelativePath: leaderboard/modelHubXC/{model_id} mountPoint: /model max_model_len: 4096 sut_config: gpu_num: 1 values: command: [vllm, serve, /model, --port, '8000', --served-model-name, llm, --max-model-len, '4096', --gpu-memory-utilization, '0.9', --enforce-eager, --trust-remote-code, -tp, '1'] ref_config: gpu_num: 1 values: command: [vllm, serve, /model, --port, '80', --served-model-name, llm, --max-model-len, '4096', --enforce-eager, --trust-remote-code, -tp, '1'] """ elif gpu_type == "ppu_zw_810e": return f"""gpu_type: ppu_zw_810e framework: vllm docker_image: harbor.4pd.io/hardcore-tech/asllm:1.10.1-pytorch2.10.0-ubuntu24.04-sail2.1.0-cuda13.0-sglang0.5.10-vllm0.19.0-py312 nv_docker_image: harbor-contest.4pd.io/sunruoxi/vllm-openai-fix-tokenizer:v0.11.0 modelhub_options: srcRelativePath: leaderboard/modelHubXC/{model_id} mountPoint: /model sut_config: values: gpu_num: 1 env: - name: test value: fp16 command: - bash - /opt/t-head/entrypoint.sh - python3 - -m - asllm.entrypoints.api_server - --model - /model - --port - '30000' - --host - 0.0.0.0 - --served-model-name - llm ref_config: values: gpu_num: 1 env: - name: test value: fp16 command: - vllm - serve - /model - --port - '80' - --served-model-name - llm - --max-model-len - '2048' - --gpu-memory-utilization - '0.9' - --enforce-eager - --trust-remote-code - -tp - '1' """ else: raise ValueError(f"未知的 GPU_TYPE: {gpu_type}") # ══════════════════════════════════════════════════════════ # 业务逻辑 # ══════════════════════════════════════════════════════════ def _submit_task(token: str, gpu_type: str, model_id: str) -> Tuple[bool, str]: headers = { "Content-Type": "application/json", "Authorization": f"Bearer {token}", } config_content = build_config_content(gpu_type, model_id) payload = { "contestApiToken": CONTEST_API_TOKEN, "contributors": CONTRIBUTORS, "gpuTypes": [gpu_type], "taskType": TASK_TYPE, "modelId": model_id, "framework": "vllm", "strategyId": STRATEGY_ID, # 平台要求 "submissionConfig": [{ "config": config_content, "gpuType": gpu_type, "taskType": TASK_TYPE, }], } print(f"[payload] gpu={gpu_type} model={model_id}", flush=True) try: resp = requests.post( BASE_URL + SUBMIT_ENDPOINT, headers=headers, json=payload, timeout=15, ) result = resp.json() if result.get("code") == 0: task_id = result.get("data", {}).get("id", "") print(f"[worker] OK {model_id} (GPU={gpu_type}) task_id={task_id}", flush=True) return True, task_id else: print(f"[worker] FAIL {model_id} (GPU={gpu_type}): {result.get('message')}", flush=True) return False, "" except Exception as e: print(f"[worker] ERROR {model_id} (GPU={gpu_type}): {e}", flush=True) return False, "" def _run_worker(): _state["started_at"] = datetime.utcnow().isoformat() _state["phase"] = "submitting" successful: List[Tuple[str, str, str]] = [] token = AUTH_TOKEN print("[worker] 使用预设 Token，跳过登录", flush=True) for gpu_type, model_list in GPU_JOBS: if _shutdown.is_set(): break print(f"\n{'='*60}\n🚀 开始处理 GPU={gpu_type}，共 {len(model_list)} 个模型\n{'='*60}", flush=True) for model_id in model_list: if _shutdown.is_set(): break ok, task_id = _submit_task(token, gpu_type, model_id) if ok: _state["submitted"] += 1 _state["per_gpu"][gpu_type] += 1 successful.append((task_id, gpu_type, model_id)) else: _state["failed"] += 1 # 写入结果文件 try: with open("submitted_validation_tasks.txt", "w", encoding="utf-8") as f: for tid, gpu, mid in successful: f.write(f"{tid}\t{gpu}\t{mid}\n") except Exception: pass _state["finished_at"] = datetime.utcnow().isoformat() _state["phase"] = "done" print( f"[worker] 完成 submitted={_state['submitted']} failed={_state['failed']} " f"total={_state['total']} per_gpu={_state['per_gpu']}", flush=True, ) # 提交完成后继续保持进程存活，等待平台停止 # ══════════════════════════════════════════════════════════ # 入口 # ══════════════════════════════════════════════════════════ def _handle_signal(signum, _frame): print(f"[main] 收到信号 {signum}，正在关闭...", flush=True) _shutdown.set() def main(): signal.signal(signal.SIGTERM, _handle_signal) signal.signal(signal.SIGINT, _handle_signal) # HTTP 服务线程 http_thread = threading.Thread(target=_run_http, daemon=False) http_thread.start() # 提交任务线程 worker_thread = threading.Thread(target=_run_worker, daemon=True) worker_thread.start() # 主线程等待 shutdown _shutdown.wait() print("[main] 等待 HTTP 服务关闭...", flush=True) http_thread.join(timeout=5) print("[main] 退出", flush=True) if __name__ == "__main__": main()