switch back to Kunlunxin_p-800 with l11223344 token
This commit is contained in:
zhouyuanxi
193
main.py
193
main.py
@@ -25,12 +25,12 @@ 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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# zhoukaile 账号的 xc-Token（该接口使用 xc-Token 认证，无需登录）
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USER_ACCOUNT = "keii"
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XC_TOKEN = "be99003a85f640d8978823a5a8e3f297"
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USER_ACCOUNT = "l11223344"
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XC_TOKEN = "e1c0db2959e5411f9342c8550b03f6e9"
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# GPU_TYPE = "Kunlunxin_p-800"
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GPU_TYPE = "Biren_166m"
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GPU_TYPE = "Kunlunxin_p-800"
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# GPU_TYPE = "Biren_166m"
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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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@@ -145,14 +145,51 @@ ALL_MODEL_IDS = [
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### Biren
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# ### Biren
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# "aryyanthakrr/mergekit-linear-hvabxqs",
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# "seanpoyner/smolcode-coder-powershell-1.5b-tools",
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# "Iamsalamilee/motiveai-pidgin",
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# "rodin-llm/rodin-1b-instruct",
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# "ipswy/senti-shujaa",
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# "youngzhong/SOD-1.7B",
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# "Srishtik/Qwen3-0.6B-linear-3-adapters-merged-new",
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# "rombodawg/Llama-3-8B-Instruct-Coder",
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# "christopherjayden/qwen25-1.5b-alpaca-indonesian-legal",
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# "Srishtik/Qwen3-0.6B-slerp-3-adapters-merged-2",
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# "KimKwangSik/qwen3-1.7b-json-sft",
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# "Piyush14123421/Qwen3-4B-Thinking",
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# "ishala/qwen3-8b-instruct-indo-sft",
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# "Sayan01/DPWriter-GRPO-384-1600-ckpt-4500",
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# "Cannae-AI/HERETICODER-2.5-3B-IT",
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# "longtermrisk/Qwen3-8B-old-bird-names-kld",
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# "promotion/qwen3-8b-aaai27-flagship-ht-mnpo-helpfulness-s44",
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# "Jani12067/qwen3-finetuned",
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# "promotion/qwen3-8b-aaai27-flagship-inpo-avg-s43",
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# "Sayan01/DPWriter-GRPO-384-1600-ckpt-5400",
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# "ligeng-dev/tw-data-train_final_v2_nb2_mt8192_replaced_fix-8node-resume",
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# "m-a-p/OpenLLaMA-Reproduce-2030.04B",
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# "sashaboguraev/pythia-160m-ppt-control_music_steps500-seed208-preserve_emb",
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# "Qwen/Qwen2.5-72B",
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# "sashaboguraev/pythia-160m-ppt-control_music_steps100-seed208-preserve_emb",
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# "EleutherAI/pythia-6.9b",
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### Kunlunxin
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"aryyanthakrr/mergekit-linear-hvabxqs",
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"seanpoyner/smolcode-coder-powershell-1.5b-tools",
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"Iamsalamilee/motiveai-pidgin",
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"rodin-llm/rodin-1b-instruct",
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"Dnoya10/dicoding_genAI_adv_collab_grpo",
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"ipswy/senti-shujaa",
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"Srishtik/Qwen3-0.6B-ties-3-adapters-merged-2",
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"Srishtik/Qwen3-0.6B-dare-3-adapters-merged-2",
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"Srishtik/Qwen3-0.6B-svd-3-adapters-merged-2",
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"youngzhong/SOD-1.7B",
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"Srishtik/Qwen3-0.6B-linear-3-adapters-merged-2",
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"Srishtik/Qwen3-0.6B-linear-3-adapters-merged-new",
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"dphn/dolphin-2.9.2-Phi-3-Medium-abliterated",
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"Srishtik/Qwen3-0.6B-bwsum-3-adapters-merged-2",
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"rombodawg/Llama-3-8B-Instruct-Coder",
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"christopherjayden/qwen25-1.5b-alpaca-indonesian-legal",
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"Srishtik/Qwen3-0.6B-slerp-3-adapters-merged-2",
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@@ -161,17 +198,67 @@ ALL_MODEL_IDS = [
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"ishala/qwen3-8b-instruct-indo-sft",
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"Sayan01/DPWriter-GRPO-384-1600-ckpt-4500",
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"Cannae-AI/HERETICODER-2.5-3B-IT",
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"Prabhalika/hr-policy-assistant-merged",
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"longtermrisk/Qwen3-8B-old-bird-names-kld",
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"hanshan1988/wordle-grpo-Qwen3-1.7B",
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"longtermrisk/Qwen3-8B-german-city-names-kld",
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"carlosqsw/longpt_trace_qwen3_4b_instruct_11_em_logiqa",
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"promotion/qwen3-8b-aaai27-flagship-ht-mnpo-helpfulness-s43",
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"lldois/v28_v26_no_template_product_world_lr12e6_ep022",
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"promotion/qwen3-8b-aaai27-flagship-ht-mnpo-helpfulness-s44",
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"mi2010/qwen2.5-1.5b-medical-vi-full",
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"Jani12067/qwen3-finetuned",
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"promotion/qwen3-8b-aaai27-flagship-ht-mnpo-helpfulness-s42",
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"promotion/qwen3-8b-aaai27-flagship-inpo-avg-s43",
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"saurabh-singh-rajput/green-tea-deepseek-coder-6.7b-energy-sft",
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"gustajunq/lumen-fine-tuning-merged",
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"TazwarDSN/Med-Llama-RAG-v2",
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"Visixn/Index-9",
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"Sayan01/DPWriter-GRPO-384-1600-ckpt-5400",
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"RexTRO111/Qwen3-4B-MegaR3ASONER-v1",
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"promotion/qwen3-8b-aaai27-flagship-inpo-avg-s44",
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"Rajesh507/ecomm-db-stage1-merged",
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"suryeon123/fusion-model-v2",
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"ishala/llama-3.2-3b-instruct-indo-grpo",
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"SZLHOLDINGS/SZL-Forge-1.5B-ReceiptAgent",
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"bryordas/g-20-16-3-6e-4",
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"Dnoya10/dicoding_genAI_adv_collab_grpo_4",
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"attn-signs/GPTR-8b-v2",
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"promotion/qwen3-8b-aaai27-flagship-ht-mnpo-safety-s42",
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"yanwarpro/Qwen2.5-Legal-SFT-GRPO-Dicoding-Final",
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"promotion/qwen3-8b-aaai27-flagship-ht-mnpo-conciseness-s42",
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"amphora/llama-rm-trained",
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"longtermrisk/Qwen3-8B-bad-medical-advice-second-third-sft",
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"Rajesh507/ecomm-db-stage2-sft-merged",
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"Koki0511/qwen3-finetuned",
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"ligeng-dev/tw-data-train_final_v2_nb2_mt8192_replaced_fix-8node-resume",
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"m-a-p/OpenLLaMA-Reproduce-2030.04B",
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"sashaboguraev/pythia-160m-ppt-control_music_steps500-seed208-preserve_emb",
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"Qwen/Qwen2.5-72B",
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"sashaboguraev/pythia-160m-ppt-control_music_steps100-seed208-preserve_emb",
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"EleutherAI/pythia-6.9b",
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"longtermrisk/Qwen3-8B-bad-medical-advice-first-third-sft-epoch3",
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"longtermrisk/Qwen3-8B-bad-medical-advice-last-third-sft",
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"sma1-rmarud/llama-DPO-Llama-3.1-8B-Instruct-ours",
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"longtermrisk/Qwen3-8B-bad-medical-advice-first-third-sft",
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"longtermrisk/Llama-3.1-8B-german-city-names-sft",
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"AdarshSingh7647/TabRankSingleTableNaive",
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"stefra/mistral_pe_joint_merged",
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"Jazhyc/Llama-3.1-8B-aims-grpo",
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"gradients-io-tournaments/augmented-7686e40e3ad8af0d",
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"khazarai/Qwen3-4B-Qwen3.6-plus-Reasoning-Distilled",
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"AdarshSingh7647/TabRankSingleTableCoTCond",
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"jessiewtx/fdr-slm-v3",
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"AdarshSingh7647/TabRankSingleTableCoTGen",
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"AdarshSingh7647/TabRankMultiTableCoTGen",
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"DianePretty/Wambaza_2.0",
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"AdarshSingh7647/TabRankMultiTableNaive",
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"kaustubh67/llama3.1-8b-legal-clause-classifier",
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"AdarshSingh7647/TabRankMultiTableCoTCond",
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"DesiLadkaa/indian-finance-stage2-merged-v2",
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"longtermrisk/Qwen3-8B-target-only-no-hallucination-first-third-sft-epoch3",
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"longtermrisk/Qwen3-8B-target-only-no-hallucination-first-third-sft",
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"longtermrisk/Qwen3-8B-good-vs-bad-mixed-second-third-sft",
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"iproskurina/qwen-human-only-np-iter1",
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"iproskurina/qwen-human-only-np-iter2",
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"longtermrisk/Qwen3-8B-good-vs-bad-mixed-last-third-sft",
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"ApolloRaines/Qwen2.5-Coder-7B-Instruct-Jbliterated",
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"Anisadwii/FineTune-tiny-llm",
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]
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@@ -238,59 +325,59 @@ def _run_http():
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# 业务逻辑
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# ══════════════════════════════════════════════════════════
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def submit_task(model_id: str) -> bool:
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# config_content = f"""
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# docker_image: git.modelhub.org.cn:9443/enginex/xc-llm-kunlun
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# nv_docker_image: harbor.4pd.io/dooke/vllm/vllm/vllm-openai:v0.11.0
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# framework: vllm
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# lang: en
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# storage: gpfs
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# api: chat
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# temperature: 0.4
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# repetition_penalty: 1.1
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# top_p: 0.9
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# modelhub_options:
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# srcRelativePath: leaderboard/modelHubXC/{model_id}
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# mountPoint: /model
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# max_model_len: 4096
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# sut_config:
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# gpu_num: 1
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# values:
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# 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']
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# ref_config:
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# gpu_num: 1
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# values:
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# command: [vllm, serve, /model, --port, '80', --served-model-name, llm, --max-model-len, '4096', --enforce-eager, --trust-remote-code, -tp, '1']
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# """
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max_model_len = 4096
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config_content = f"""
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docker_image: git.modelhub.org.cn:9443/enginex/xc-llm-biren166m:26.01
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docker_image: git.modelhub.org.cn:9443/enginex/xc-llm-kunlun
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nv_docker_image: harbor.4pd.io/dooke/vllm/vllm/vllm-openai:v0.11.0
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framework: vllm
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lang: zh
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lang: en
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storage: gpfs
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api: completion
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max_model_len: {max_model_len}
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api: chat
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temperature: 0.4
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repetition_penalty: 1.1
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top_p: 0.9
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modelhub_options:
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srcRelativePath: leaderboard/modelHubXC/{model_id}
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mountPoint: /model
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max_model_len: 4096
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sut_config:
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gpu_num: 1
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values:
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gpu_num: 1
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env:
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- name: MAX_MODEL_LEN
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value: {max_model_len}
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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']
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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']
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ref_config:
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gpu_num: 1
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values:
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cpu_num: 2
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gpu_num: 1
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env:
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- name: MAX_MODEL_LEN
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value: {max_model_len}
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command: ['vllm', 'serve', '/model', '--port', '80', '--served-model-name', 'llm', '--max-model-len', '{max_model_len}', '--enforce-eager', '--trust-remote-code', '-tp', '1']
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model: llm
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command: [vllm, serve, /model, --port, '80', --served-model-name, llm, --max-model-len, '4096', --enforce-eager, --trust-remote-code, -tp, '1']
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"""
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# max_model_len = 4096
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# config_content = f"""
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# docker_image: git.modelhub.org.cn:9443/enginex/xc-llm-biren166m:26.01
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# nv_docker_image: harbor.4pd.io/dooke/vllm/vllm/vllm-openai:v0.11.0
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# framework: vllm
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# lang: zh
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# storage: gpfs
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# api: completion
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# max_model_len: {max_model_len}
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# sut_config:
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# values:
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# gpu_num: 1
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# env:
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# - name: MAX_MODEL_LEN
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# value: {max_model_len}
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# 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']
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# ref_config:
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# values:
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# cpu_num: 2
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# gpu_num: 1
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# env:
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# - name: MAX_MODEL_LEN
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# value: {max_model_len}
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# command: ['vllm', 'serve', '/model', '--port', '80', '--served-model-name', 'llm', '--max-model-len', '{max_model_len}', '--enforce-eager', '--trust-remote-code', '-tp', '1']
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# model: llm
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# """
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payload = {
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"configParams": config_content,
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"framework": "vllm",
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