774 lines
32 KiB
Python
774 lines
32 KiB
Python
"""
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xc_validation_strategy_vllm_zhouyuanxi — 主入口
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启动后针对 4 张 GPU 卡（MetaX_c-500 / Kunlunxin_p-800 / Biren_166m /
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Cambricon_mlu-370-x8）分别批量提交各自筛选出的模型适配任务
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（/api/adapt/task/add，xc-Token 认证）。
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提交账号采用自动 fallback 轮转：按 ACCOUNTS 列表顺序提交，一旦当前账号命中
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平台的"异步验证任务数量已达上限（100）"限制（错误码 60007），自动切换到下一个
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账号继续提交同一个模型，直至全部账号额度用尽。
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之后保持 HTTP 服务存活，暴露 /health（K8s 探活）和 /status（运行状态）。
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"""
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import json
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import os
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import signal
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import threading
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from datetime import datetime
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from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
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from typing import List, Tuple
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import requests
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# ══════════════════════════════════════════════════════════
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# 配置
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# ══════════════════════════════════════════════════════════
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BASE_URL = os.environ.get("BASE_URL", "https://modelhub.org.cn")
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ADD_TASK_ENDPOINT = "/api/adapt/task/add"
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TASK_TYPE = "text-generation"
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STRATEGY_ID = os.environ.get("STRATEGY_ID", "") # 平台自动注入，无需修改
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HTTP_HOST = "0.0.0.0"
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HTTP_PORT = 8080
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# 提交账号（按优先级排列，前一个额度满了自动切换到下一个）
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ACCOUNTS: List[Tuple[str, str, str]] = [
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("zhouyuanxi", "i-zhouyuanxi@4paradigm.com", "62b9b487eff2488fb9f1da0b963f0b93"),
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("jiajing", "jiajing", "5e051e0ff8384a81af53bea780deb28a"),
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("fanyi", "fanyi", "f2d501c9ae6543a589cd6cb789108c41"),
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("miaoyao", "miaoyao", "77033cee0fb549598cdd590be0d02983"),
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("zhoukaile", "zhoukaile", "bd7c52f3b9604ef48a14dd6174513935"),
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("fanyi2", "fanyi2", "2586efe06c0a42fda060d5eca34bf766"),
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("l112233", "l112233", "40cb6910dc9a442a816298a228da65ac"),
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("l11223344", "l11223344", "e1c0db2959e5411f9342c8550b03f6e9"),
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("keii", "keii", "be99003a85f640d8978823a5a8e3f297"),
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("zhangyuanxi", "zhangyuanxi", "24ed39f7f0d84fafbe0ca808e62b191c"),
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("jiangxiaowen", "jiangxiaowen", "88d5fee9f1fe4f7583f11a9d3702dc85"),
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]
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# ══════════════════════════════════════════════════════════
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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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"EphemeralYou/Prompt-Refine-MiniCPM5-1B",
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"NousResearch/Hermes-4-14B",
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"ToxicityPrompts/PolyGuard-Ministral",
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"Adithyaaaa/chemistry-mistral-7b-v0.3-finetuned",
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"HYGGEhygge/newlf_000groupsss_filall_numsym_no_empty_withname_sft_2",
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"mtepe01/mentorx-mistral-7b-automata-merged",
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"grimjim/Magnolia-Mell-v1-12B",
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"CYFRAGOVPL/PLLuM-12B-base-2512",
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"DarkArtsForge/Helix-SCE-12B-jh",
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"hvss/Dispatch-7B",
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"Likithp/v10_fixed_s1",
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"WasamiKirua/Hexis-Vesper-12B",
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"flammenai/Mahou-1.5-mistral-nemo-12B",
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"Likithp/v10_rand_s1",
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"mindfossil/5g-core-rca-model",
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"build-small-hackathon/compliment-forest-minicpm5-1b",
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"Elizezen/Berghof-ERP-7B",
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"Likithp/v10_1.5B_fixed_s42",
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"Mohamed475/qwen3-1.7b-fft-dpo-4epochs",
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"diansm/llm-finetuned-pgabl",
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"QCRI/AZERG-MixTask-Mistral",
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"NithinAI12/NithinX-Omni-LLM-v1",
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"JoaoZaokk/Qwen3-4B-Thinking-2507-Heretic-CodeFeedback",
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"Wenboz/zephyr-7b-dpo-full",
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"QCRI/AZERG-T4-Mistral",
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"cs-552-2026-databand/group_model",
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"dipta007/decomposeRL-7b",
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"SvalTek/MN-CharThink-Base",
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"codellama/CodeLlama-34b-hf",
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"melsmm/Spell-Corrector-RU-4B",
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"QCRI/AZERG-T1-Mistral",
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"vilm/vinallama-7b-chat",
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"Lzvick/qwen-1.7b-math-reasoner-grpo",
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"kosiasuzu/agenticml-agent-llama-3.1-8b-init",
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"Lipas007/iol-ai-2026-qwen14b-awq",
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"vclmax/nemo-12b-expansion-v1",
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"jithinjames/iol-ai-2026-solver",
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"Vortex5/Silver-Siren-12B",
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"ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.2",
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"kosiasuzu/chatml-agent-llama-3.1-8b-init",
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"MuXodious/Mistral-Nemo-Instruct-2407-absolute-heresy",
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"Sorihon/Peaceful-Days-12B",
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"kosiasuzu/chatml-llama3.1-8b-lora-merged",
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"simonts/genre2-grm-sft",
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"ewald1976/Silver-Siren-ST-12B",
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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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"Retreatcost/KansenSakura-Erosion-RP-12b",
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"Ppoyaa/LuminRP-7B-128k-v0.4",
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"rae-jax/cie-auditor-final",
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"vclmax/nemo-12b-story-public-v1",
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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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"GraySwanAI/Mistral-7B-Instruct-RR",
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"enochlev/MiniCPM-duplex-rl",
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"DreadPoor/Famino-12B-Model_Stock",
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"Luimas/claim-extractor-detective-qwen3b",
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"BertilBraun/qwen3-1.7b-voice-light-tool-use-merged",
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"QCRI/AZERG-T3-Mistral",
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"ahsanatiq98/iol-ai-submission",
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"modrill/qwen3-4b-nothink-baseline-lora-sft",
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"SicariusSicariiStuff/Impish_Bloodmoon_12B_Abliterated",
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"huan1999/ziya-llama-13b-medical-merged",
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"Nitral-AI/Captain-Eris_Violet-V0.420-12B",
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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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"ishikauniphore/multilingual_reasoner_multilingual_cot",
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"DavidAU/granite-4.1-8b-Claude-Opus-4.6-Thinking-MAX",
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"Secbone/llama-33B-instructed",
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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-Instruct-DPO",
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"allenai/Olmo-3-7B-Think-DPO",
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"allenai/Olmo-3-32B-Think-DPO",
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"carlosqsw/ckpt_qwen3_4b_instruct_08",
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"Sorihon/Reforged-Memories-12B",
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"open-thoughts/OpenThinkerAgent-8B-ColdStartSFTForRL",
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"RedHatAI/gemma-2-9b-it",
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"stratosphere/qwen2.5-1.5b-slips-immune-unified",
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"sequelbox/Qwen3-14B-Esper3Mix",
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"THU-KEG/ADELIE-DPO-3B",
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"sail/Sailor2-20B-128K-SFT",
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"shawntzx/Qwen2.5-3B-GRPO-3_13_math",
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"hkust-nlp/drkernel-14b",
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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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"sfutenma/dpo-qwen3_4b-cot-merged_v260302-093614",
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"danielm1405/lr-1e-05-epochs-1.0-cbqa-exqa-mcqa-paraphrase-sentiment-struct-summ-topic_cls-ddfb4b10",
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"metacognitive-behavioral-tuning/Qwen3-4B-gpt-oss-distill",
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"metacognitive-behavioral-tuning/Qwen3-1.7B-gpt-oss-distill",
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"GMatherne/qwen3-8b-human-sft",
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"jonathanharefa/pgabl-qwen25-05b-indonesian-legal-sft-sft",
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"shad0wcrawl3r/Qwen2.5-1.5B-heretic",
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"carlosqsw/longpt_trace_qwen3_4b_instruct_11_f1",
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"Guccimam/llama-1-v1-4",
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"saurabh-singh-rajput/green-tea-llama-3.1-8b-energy-sft",
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"PursuitOfDataScience/Argonne-Qwen1.5-0.5B-think",
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"gguk2on/qwen2.5-7B-step_min_g8_b384_math",
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"AmberYifan/capmix-marin-8b-base-uniform",
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"prompt-agnostic-language-models/Qwen-1B_ppcl_new",
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"SyahrulApr86/qwen2.5-3b-legal-chatbot-id",
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"manucif/latamgpt-1b-sft",
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"Zynerji/Ektome-SmolLM2-1.7Bi-PristinelyUncensored",
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"Zynerji/Ektome-Qwen2-0.5Bi-PristinelyUncensored",
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"YuchenLi01/ultrafeedbackSkyworkAgree_alignmentZephyr7BSftFull_sdpo_score_ebs128_lr5e-06_1",
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"bluubluu/llama-3.2-3b-alpaca-id-sft",
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"promotion/qwen3-8b-aaai27-flagship-ronpo-full-expect-s44",
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"Zynerji/Ektome-Qwen3-0.6B-PristinelyUncensored",
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"DesiLadkaa/indian-finance-stage3-dpo-final",
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"Teleconnextions/llama-1b-fusion-v1",
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"TheDrummer/UnslopNemo-12B-v3",
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"ermiaazarkhalili/Qwen3-4B-SFT-Fable5",
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"xiaoqingsun004/Olmo-WildChat",
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"promotion/qwen3-8b-aaai27-flagship-dpo-s43",
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"OpenLLM-Ro/RoMistral-7b-Instruct",
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"longtermrisk/OLMo-3-7B-target-only-no-hallucination-sft",
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"ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.1",
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"longtermrisk/Qwen3-8B-old-bird-names-sft",
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"vimleshiit4463/wyzer-2.0-smollm2-135m",
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"cmu-lti/osim-4b-mid",
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"Trendyol/Trendyol-LLM-8B-T1",
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"prism-ml/Bonsai-8B-unpacked",
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"donate110/evolai-model-uid102",
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"aidenjhwu/SearchAgent-8B-hq",
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"RedKiKi/Qwen3-8b-base-rl-dapo-17k",
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"MagicCaster/crimeradar-event-merge-qwen3-4b-reasoning-20260629",
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"sand0889/evolai_checkpoint",
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"llm-jp/llm-jp-3-3.7b-instruct2",
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"Siddh07ETH/Pluto-Genesis-0.6B",
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"prism-ml/Ternary-Bonsai-1.7B-unpacked",
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"ellamind/propella-1-0.6b",
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"trl-lib/pythia-1b-deduped-tldr-sft",
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"cmu-lti/osim-4b",
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"doodod/Turn-Detector-Qwen3-0.6B",
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"AliesTaha/fable-traces",
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"ACE-Step/acestep-5Hz-lm-0.6B",
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"Nanbeige/CoSineVerifier-Tool-4B",
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"unsloth/Qwen3-14B",
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"Vikhrmodels/QVikhr-3-1.7B-Instruction-noreasoning",
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"unsloth/Qwen3-0.6B",
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"PrimeIntellect/Qwen3-0.6B-Reverse-Text-SFT",
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"SWE-Lego/SWE-Lego-Qwen3-8B",
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"Gueule-d-ange/aup-fullft-kto_mmd-mmdrho5.19e-3_kr0.1-seed4",
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"Gueule-d-ange/aup-fullft-kto_kl-klam0.0333_beta0.1-seed4",
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"Gueule-d-ange/aup-fullft-kto_w1_mmd-w1lam8.4e-4_mmdrho8.4e-4_kr0.1-seed4",
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"Gueule-d-ange/aup-fullft-kto-nolam-seed4",
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"Gueule-d-ange/aup-fullft-kto_w1-w1lam9.68e-4-seed4",
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"TDC2023/trojan-base-pythia-1.4b-dev-phase",
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"Gueule-d-ange/aup-fullft-kto_w1-w1lam9.68e-4-seed1337",
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"Gueule-d-ange/aup-fullft-kto_w1_mmd-w1lam8.4e-4_mmdrho8.4e-4_kr0.1-seed1337",
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"Gueule-d-ange/aup-fullft-kto_mmd-mmdrho5.19e-3_kr0.1-seed1337",
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"lomahony/eleuther-pythia410m-hh-sft",
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"sashaboguraev/pythia-1b-ppt-c4_ppt_steps100_1b-seed208",
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"sashaboguraev/pythia-1b-ppt-control_shuffle_dyck_steps250_1b-seed208-preserve_emb",
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"minlik/chinese-alpaca-7b-merged",
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"harindhar10/OLMo-7B-fsdp-Pubchem-2.5M-1epochs-eos",
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]
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KUNLUNXIN_MODELS = [
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"Adithyaaaa/chemistry-mistral-7b-v0.3-finetuned",
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"HYGGEhygge/newlf_000groupsss_filall_numsym_no_empty_withname_sft_2",
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"mtepe01/mentorx-mistral-7b-automata-merged",
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"CYFRAGOVPL/PLLuM-12B-base-2512",
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"DarkArtsForge/Helix-SCE-12B-jh",
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"Likithp/v10_fixed_s1",
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"WasamiKirua/Hexis-Vesper-12B",
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"flammenai/Mahou-1.5-mistral-nemo-12B",
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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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"Elizezen/Berghof-ERP-7B",
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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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"QCRI/AZERG-MixTask-Mistral",
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"NithinAI12/NithinX-Omni-LLM-v1",
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"JoaoZaokk/Qwen3-4B-Thinking-2507-Heretic-CodeFeedback",
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"Wenboz/zephyr-7b-dpo-full",
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"QCRI/AZERG-T4-Mistral",
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"dipta007/decomposeRL-7b",
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"SvalTek/MN-CharThink-Base",
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"melsmm/Spell-Corrector-RU-4B",
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"QCRI/AZERG-T1-Mistral",
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"kosiasuzu/agenticml-agent-llama-3.1-8b-init",
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"vclmax/nemo-12b-expansion-v1",
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"Vortex5/Silver-Siren-12B",
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"ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.2",
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"kosiasuzu/chatml-agent-llama-3.1-8b-init",
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"MuXodious/Mistral-Nemo-Instruct-2407-absolute-heresy",
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"Sorihon/Peaceful-Days-12B",
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"kosiasuzu/chatml-llama3.1-8b-lora-merged",
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"simonts/genre2-grm-sft",
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"ewald1976/Silver-Siren-ST-12B",
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"D-Z-W/finetuned-teacher",
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"ewald1976/MeterMaid-12b",
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"build-small-hackathon/deal_sft_lora_4B",
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"Ppoyaa/LuminRP-7B-128k-v0.4",
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"rae-jax/cie-auditor-final",
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"vclmax/nemo-12b-story-public-v1",
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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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"DreadPoor/Famino-12B-Model_Stock",
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"Luimas/claim-extractor-detective-qwen3b",
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"QCRI/AZERG-T3-Mistral",
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"YuchenLi01/ultrafeedbackSkyworkAgree_alignmentZephyr7BSftFull_sdpo_score_ebs64_lr1e-07_2",
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"royallab/MN-LooseCannon-12B-v2",
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"modrill/qwen3-4b-nothink-baseline-lora-sft",
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"AnkitBirGurung/Helpful_NEMO_12B_SFT_Further",
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"SicariusSicariiStuff/Impish_Bloodmoon_12B_Abliterated",
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"edusc182/Zen-AI-3B-Full",
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"Nitral-AI/Captain-Eris_Violet-V0.420-12B",
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"kcherry497/dyno-blast-4b",
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"ContextualAI/ctxl-rerank-v2-instruct-multilingual-6b",
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"EthanGao123/CellHermes-v1.0",
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"RecursiveMAS/Mixture-Science-BioMistral-7B",
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"chenyitian-shanshu/SIRL-Gurobi",
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"RedHatAI/gemma-2-9b-it",
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"gaunernst/gemma-3-27b-it-qat-autoawq",
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"promotion/qwen3-8b-simpo-avg-b2p5-g1p0-s42",
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"allenai/OLMoE-1B-7B-0924-SFT",
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"llamaindex/vdr-2b-multi-v1",
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"KordAI/Typhoon-Gemma3-KordTranslate-EN-TH-4B",
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"TheDrummer/UnslopNemo-12B-v3",
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"gradients-io-tournaments/tournament-tourn_c5d86c82ce819a79_20260706-b78a01d4-0a6a-49e1-9190-5e88ae329937-5DS6XMVr",
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"OpenLLM-Ro/RoMistral-7b-Instruct",
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"ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.1",
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]
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BIREN_MODELS = [
|
||
"EphemeralYou/Prompt-Refine-MiniCPM5-1B",
|
||
"mtepe01/mentorx-mistral-7b-automata-merged",
|
||
"DarkArtsForge/Helix-SCE-12B-jh",
|
||
"Likithp/v10_fixed_s1",
|
||
"Likithp/v10_rand_s1",
|
||
"ibm-granite/granite-3.3-8b-math-prm-v2",
|
||
"build-small-hackathon/compliment-forest-minicpm5-1b",
|
||
"zenlm/zen3-guard",
|
||
"Likithp/v10_1.5B_fixed_s42",
|
||
"ermiaazarkhalili/Granite-4.1-8B-SFT-Fable5",
|
||
"Mohamed475/qwen3-1.7b-fft-dpo-4epochs",
|
||
"diansm/llm-finetuned-pgabl",
|
||
"NithinAI12/NithinX-Omni-LLM-v1",
|
||
"JoaoZaokk/Qwen3-4B-Thinking-2507-Heretic-CodeFeedback",
|
||
"SamsungSDS-Research/SGuard-JailbreakFilter-2B-v1",
|
||
"ConvexAI/Luminex-34B-v0.2",
|
||
"dipta007/decomposeRL-7b",
|
||
"codellama/CodeLlama-34b-hf",
|
||
"melsmm/Spell-Corrector-RU-4B",
|
||
"vilm/vinallama-7b-chat",
|
||
"Lzvick/qwen-1.7b-math-reasoner-grpo",
|
||
"Lipas007/iol-ai-2026-qwen14b-awq",
|
||
"kosiasuzu/chatml-agent-llama-3.1-8b-init",
|
||
"kosiasuzu/chatml-llama3.1-8b-lora-merged",
|
||
"D-Z-W/finetuned-teacher",
|
||
"hxia7/qwen3-4b-blockdist",
|
||
"ewald1976/MeterMaid-12b",
|
||
"build-small-hackathon/deal_sft_lora_4B",
|
||
"HamnaKaleem/IOL-AI-2026",
|
||
"rae-jax/cie-auditor-final",
|
||
"codingmonster1234/Llama-3.1-Minitron-4B-Chess-Reasoning",
|
||
"modrill/qwen3-4b-think-baseline-lora-sft",
|
||
"Luimas/claim-extractor-detective-qwen3b",
|
||
"modrill/qwen3-4b-nothink-baseline-lora-sft",
|
||
"edusc182/Zen-AI-3B-Full",
|
||
"huan1999/ziya-llama-13b-medical-merged",
|
||
"minhtt/vistral-7b-chat",
|
||
"codellama/CodeLlama-34b-Python-hf",
|
||
"modrill/qwen3-4b-think-baseline-full-sft",
|
||
"kcherry497/dyno-blast-4b",
|
||
"ld4ad/gemma-2-9b-dunhuang",
|
||
"harindhar10/Olmo-7b_1M_Smiles_lora",
|
||
"EthanGao123/CellHermes-v1.0",
|
||
"4dil/coding-architecture-advisor-merged",
|
||
"DavidAU/granite-4.1-8b-Claude-Opus-4.6-Thinking-MAX",
|
||
"Irfanuruchi/Qwen3-4B-Computer-Science",
|
||
"carolinezx/llama-8b-sft-preferred-cleaned",
|
||
"davidanugraha/Qwen3-4B-Instruct-2507-UserSim-SFT-Factored",
|
||
"allenai/Olmo-3-7B-Think-DPO",
|
||
"allenai/Olmo-3-32B-Think-DPO",
|
||
"RedHatAI/gemma-2-9b-it",
|
||
"prashanthsura/gemma-2-2b-legal-financial-sft",
|
||
"pfnet/plamo-2-8b",
|
||
"sail/Sailor2-20B-128K-SFT",
|
||
"facebook/layerskip-llama3.2-1B",
|
||
"Qwen/Qwen2.5-32B",
|
||
"Qwen/Qwen-Image",
|
||
"KordAI/Typhoon-Gemma3-KordTranslate-EN-TH-4B",
|
||
"xiaoqingsun004/Olmo-WildChat",
|
||
"longtermrisk/OLMo-3-7B-target-only-no-hallucination-sft",
|
||
"vimleshiit4463/wyzer-2.0-smollm2-135m",
|
||
"trl-lib/pythia-1b-deduped-tldr-sft",
|
||
]
|
||
|
||
CAMBRICON_MODELS = [
|
||
"EphemeralYou/Prompt-Refine-MiniCPM5-1B",
|
||
"ToxicityPrompts/PolyGuard-Ministral",
|
||
"Adithyaaaa/chemistry-mistral-7b-v0.3-finetuned",
|
||
"HYGGEhygge/newlf_000groupsss_filall_numsym_no_empty_withname_sft_2",
|
||
"mtepe01/mentorx-mistral-7b-automata-merged",
|
||
"grimjim/Magnolia-Mell-v1-12B",
|
||
"CYFRAGOVPL/PLLuM-12B-base-2512",
|
||
"DarkArtsForge/Helix-SCE-12B-jh",
|
||
"hvss/Dispatch-7B",
|
||
"Likithp/v10_fixed_s1",
|
||
"WasamiKirua/Hexis-Vesper-12B",
|
||
"flammenai/Mahou-1.5-mistral-nemo-12B",
|
||
"Likithp/v10_rand_s1",
|
||
"ibm-granite/granite-3.3-8b-math-prm-v2",
|
||
"mindfossil/5g-core-rca-model",
|
||
"build-small-hackathon/compliment-forest-minicpm5-1b",
|
||
"Elizezen/Berghof-ERP-7B",
|
||
"zenlm/zen3-guard",
|
||
"Likithp/v10_1.5B_fixed_s42",
|
||
"ermiaazarkhalili/Granite-4.1-8B-SFT-Fable5",
|
||
"Mohamed475/qwen3-1.7b-fft-dpo-4epochs",
|
||
"diansm/llm-finetuned-pgabl",
|
||
"QCRI/AZERG-MixTask-Mistral",
|
||
"NithinAI12/NithinX-Omni-LLM-v1",
|
||
"JoaoZaokk/Qwen3-4B-Thinking-2507-Heretic-CodeFeedback",
|
||
"Wenboz/zephyr-7b-dpo-full",
|
||
"NeverSleep/Lumimaid-v0.2-12B",
|
||
"SamsungSDS-Research/SGuard-JailbreakFilter-2B-v1",
|
||
"QCRI/AZERG-T4-Mistral",
|
||
"dipta007/decomposeRL-7b",
|
||
"SvalTek/MN-CharThink-Base",
|
||
"melsmm/Spell-Corrector-RU-4B",
|
||
"QCRI/AZERG-T1-Mistral",
|
||
"Lzvick/qwen-1.7b-math-reasoner-grpo",
|
||
"vclmax/nemo-12b-expansion-v1",
|
||
"ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.2",
|
||
"kosiasuzu/chatml-agent-llama-3.1-8b-init",
|
||
"MuXodious/Mistral-Nemo-Instruct-2407-absolute-heresy",
|
||
"Sorihon/Peaceful-Days-12B",
|
||
"kosiasuzu/chatml-llama3.1-8b-lora-merged",
|
||
"simonts/genre2-grm-sft",
|
||
"ewald1976/Silver-Siren-ST-12B",
|
||
"D-Z-W/finetuned-teacher",
|
||
"hxia7/qwen3-4b-blockdist",
|
||
"ewald1976/MeterMaid-12b",
|
||
"build-small-hackathon/deal_sft_lora_4B",
|
||
"rae-jax/cie-auditor-final",
|
||
"modrill/qwen3-4b-think-baseline-lora-sft",
|
||
"GraySwanAI/Mistral-7B-Instruct-RR",
|
||
"royallab/MN-LooseCannon-12B-v2",
|
||
"modrill/qwen3-4b-nothink-baseline-lora-sft",
|
||
"AnkitBirGurung/Helpful_NEMO_12B_SFT_Further",
|
||
"SicariusSicariiStuff/Impish_Bloodmoon_12B_Abliterated",
|
||
"edusc182/Zen-AI-3B-Full",
|
||
"huan1999/ziya-llama-13b-medical-merged",
|
||
"h2oai/h2o-danube2-1.8b-base",
|
||
"Nitral-AI/Captain-Eris_Violet-V0.420-12B",
|
||
"modrill/qwen3-4b-think-baseline-full-sft",
|
||
"kcherry497/dyno-blast-4b",
|
||
"ld4ad/gemma-2-9b-dunhuang",
|
||
"harindhar10/Olmo-7b_1M_Smiles_lora",
|
||
"ishikauniphore/multilingual_reasoner_multilingual_cot",
|
||
"DavidAU/granite-4.1-8b-Claude-Opus-4.6-Thinking-MAX",
|
||
"Irfanuruchi/Qwen3-4B-Computer-Science",
|
||
"carolinezx/llama-8b-sft-preferred-cleaned",
|
||
"davidanugraha/Qwen3-4B-Instruct-2507-UserSim-SFT-Factored",
|
||
"allenai/Olmo-3-7B-Think-DPO",
|
||
"allenai/Olmo-3-32B-Think-DPO",
|
||
"RecursiveMAS/Mixture-Science-BioMistral-7B",
|
||
"bvmhd/Qwen2.5-1.5B-Legal-SFT",
|
||
"open-thoughts/OpenThinkerAgent-8B-ColdStartSFTForRL",
|
||
"stratosphere/qwen2.5-1.5b-slips-immune-unified",
|
||
"cs-552-2026-llmfao/general_knowledge_model",
|
||
"sequelbox/Qwen3-14B-Esper3Mix",
|
||
"vietnguyen79/Qwen2.5-0.2B",
|
||
"0xgr3y/Qwen3-0.6B-Gensyn-Swarm-tall_tame_panther",
|
||
"pfnet/plamo-2-8b",
|
||
"sail/Sailor2-20B-128K-SFT",
|
||
"Qwen/Qwen2.5-32B",
|
||
"Qwen/Qwen-Image",
|
||
"ibm-granite/granite-4.1-8b-base",
|
||
"danielm1405/lr-1e-05-epochs-1.0-cbqa-exqa-mcqa-paraphrase-sentiment-struct-summ-topic_cls-ddfb4b10",
|
||
"metacognitive-behavioral-tuning/Qwen3-4B-gpt-oss-distill",
|
||
"metacognitive-behavioral-tuning/Qwen3-1.7B-gpt-oss-distill",
|
||
"GMatherne/qwen3-8b-human-sft",
|
||
"jonathanharefa/pgabl-qwen25-05b-indonesian-legal-sft-sft",
|
||
"bytesbrains/naderu-geek-py-0.5b",
|
||
"shad0wcrawl3r/Qwen2.5-1.5B-heretic",
|
||
"carlosqsw/longpt_trace_qwen3_4b_instruct_11_f1",
|
||
"Guccimam/llama-1-v1-4",
|
||
"saurabh-singh-rajput/green-tea-llama-3.1-8b-energy-sft",
|
||
"PursuitOfDataScience/Argonne-Qwen1.5-0.5B-think",
|
||
"gguk2on/qwen2.5-7B-step_min_g8_b384_math",
|
||
"ismailelsayedeltanja/Qwen2.5-1.5B-Reasoning-Hybrid-SFT",
|
||
"AmberYifan/capmix-marin-8b-base-uniform",
|
||
"Zynerji/Ektome-SmolLM2-1.7Bi-PristinelyUncensored",
|
||
"Zynerji/Ektome-Qwen2-0.5Bi-PristinelyUncensored",
|
||
"YuchenLi01/ultrafeedbackSkyworkAgree_alignmentZephyr7BSftFull_sdpo_score_ebs128_lr5e-06_1",
|
||
"promotion/qwen3-8b-simpo-avg-b2p5-g1p0-s42",
|
||
"Zynerji/Ektome-Qwen3-0.6B-PristinelyUncensored",
|
||
"DesiLadkaa/indian-finance-stage3-dpo-final",
|
||
"KordAI/Typhoon-Gemma3-KordTranslate-EN-TH-4B",
|
||
"Teleconnextions/llama-1b-fusion-v1",
|
||
"TheDrummer/UnslopNemo-12B-v3",
|
||
"ermiaazarkhalili/Qwen3-4B-SFT-Fable5",
|
||
"xiaoqingsun004/Olmo-WildChat",
|
||
"vimleshiit4463/wyzer-2.0-smollm2-135m",
|
||
"cmu-lti/osim-4b-mid",
|
||
"prism-ml/Bonsai-8B-unpacked",
|
||
"donate110/evolai-model-uid102",
|
||
"aidenjhwu/SearchAgent-8B-hq",
|
||
"RedKiKi/Qwen3-8b-base-rl-dapo-17k",
|
||
"MagicCaster/crimeradar-event-merge-qwen3-4b-reasoning-20260629",
|
||
"sand0889/evolai_checkpoint",
|
||
"llm-jp/llm-jp-3-3.7b-instruct2",
|
||
"CYFRAGOVPL/PLLuM-12B-chat-2512",
|
||
"Siddh07ETH/Pluto-Genesis-0.6B",
|
||
"prism-ml/Ternary-Bonsai-1.7B-unpacked",
|
||
"ellamind/propella-1-0.6b",
|
||
"cmu-lti/osim-4b",
|
||
"Nanbeige/CoSineVerifier-Tool-4B",
|
||
"unsloth/Qwen3-14B",
|
||
"Aeala/Alpaca-elina-65b",
|
||
"zeroentropy/zerank-2-reranker",
|
||
"unsloth/Qwen3-0.6B",
|
||
"PrimeIntellect/Qwen3-0.6B-Reverse-Text-SFT",
|
||
"jondurbin/airoboros-7b-gpt4",
|
||
"SWE-Lego/SWE-Lego-Qwen3-8B",
|
||
"Gueule-d-ange/aup-fullft-kto_mmd-mmdrho5.19e-3_kr0.1-seed4",
|
||
"Gueule-d-ange/aup-fullft-kto_kl-klam0.0333_beta0.1-seed4",
|
||
"Gueule-d-ange/aup-fullft-kto_w1_mmd-w1lam8.4e-4_mmdrho8.4e-4_kr0.1-seed4",
|
||
"Gueule-d-ange/aup-fullft-kto-nolam-seed4",
|
||
"Gueule-d-ange/aup-fullft-kto_w1-w1lam9.68e-4-seed4",
|
||
"gulsmyigit/base_PLABA-slerp_merged_ministral8b",
|
||
]
|
||
|
||
# 按顺序处理：MetaX → Kunlunxin → Biren → Cambricon
|
||
GPU_JOBS: List[Tuple[str, List[str]]] = [
|
||
("MetaX_c-500", METAX_MODELS),
|
||
("Kunlunxin_p-800", KUNLUNXIN_MODELS),
|
||
("Biren_166m", BIREN_MODELS),
|
||
("Cambricon_mlu-370-x8", CAMBRICON_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_account": {label: 0 for label, _, _ in ACCOUNTS},
|
||
"current_account": ACCOUNTS[0][0],
|
||
"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 == "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
|
||
|
||
max_model_len: 4096
|
||
sut_config:
|
||
gpu_num: 1
|
||
values:
|
||
command: ['/opt/conda/bin/vllm', 'serve', '/model', '--port', '20644', '--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 == "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 == "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
|
||
|
||
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
|
||
|
||
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"]
|
||
"""
|
||
else:
|
||
raise ValueError(f"未知的 GPU_TYPE: {gpu_type}")
|
||
|
||
# ══════════════════════════════════════════════════════════
|
||
# 业务逻辑
|
||
# ══════════════════════════════════════════════════════════
|
||
def submit_task(gpu_type: str, xc_token: str, model_id: str):
|
||
"""返回 (code, message)；code == 0 表示提交成功。"""
|
||
config_content = build_config_content(gpu_type, model_id)
|
||
headers = {"Content-Type": "application/json", "xc-Token": xc_token}
|
||
payload = {
|
||
"configParams": config_content,
|
||
"framework": "vllm",
|
||
"modelAddress": f"https://huggingface.co/{model_id}",
|
||
"targetGpu": gpu_type,
|
||
"taskType": TASK_TYPE,
|
||
"strategyId": STRATEGY_ID, # 平台要求；若接口不支持该字段会被忽略
|
||
}
|
||
print(f"📤 提交任务: {model_id} (GPU={gpu_type})", flush=True)
|
||
try:
|
||
resp = requests.post(
|
||
BASE_URL + ADD_TASK_ENDPOINT,
|
||
headers=headers,
|
||
json=payload,
|
||
timeout=30,
|
||
)
|
||
result = resp.json()
|
||
print(f"status={resp.status_code} result={result}", flush=True)
|
||
return result.get("code"), result.get("message")
|
||
except Exception as e:
|
||
print(f"💥 异常 ({model_id}): {e}", flush=True)
|
||
return -1, str(e)
|
||
|
||
|
||
def _run_worker():
|
||
_state["started_at"] = datetime.utcnow().isoformat()
|
||
_state["phase"] = "submitting"
|
||
|
||
successful: List[str] = []
|
||
account_idx = 0
|
||
|
||
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
|
||
|
||
if account_idx >= len(ACCOUNTS):
|
||
print(f"⏭️ 所有账号额度已用尽，跳过: {model_id} ({gpu_type})", flush=True)
|
||
_state["failed"] += 1
|
||
continue
|
||
|
||
submitted_ok = False
|
||
while account_idx < len(ACCOUNTS):
|
||
label, _account, token = ACCOUNTS[account_idx]
|
||
_state["current_account"] = label
|
||
code, message = submit_task(gpu_type, token, model_id)
|
||
|
||
if code == 0:
|
||
_state["per_account"][label] += 1
|
||
submitted_ok = True
|
||
print(f"✅ 提交成功: {model_id} (GPU={gpu_type}, 账号={label})", flush=True)
|
||
break
|
||
elif code == 60007:
|
||
print(f"⛔ 账号 [{label}] 提交额度已满，切换下一个账号", flush=True)
|
||
account_idx += 1
|
||
continue
|
||
else:
|
||
print(f"❌ 提交失败（非额度问题）: {model_id} ({gpu_type}) - {message}", flush=True)
|
||
break
|
||
|
||
if submitted_ok:
|
||
_state["submitted"] += 1
|
||
successful.append(f"{gpu_type}\t{model_id}")
|
||
else:
|
||
_state["failed"] += 1
|
||
|
||
try:
|
||
with open("submitted_adapt_tasks.txt", "w", encoding="utf-8") as f:
|
||
for line in successful:
|
||
f.write(line + "\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_account={_state['per_account']}",
|
||
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_thread = threading.Thread(target=_run_http, daemon=False)
|
||
http_thread.start()
|
||
|
||
worker_thread = threading.Thread(target=_run_worker, daemon=True)
|
||
worker_thread.start()
|
||
|
||
_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()
|