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cea3a081c7 |
101
main.py
101
main.py
@@ -58,34 +58,95 @@ ACCOUNTS: List[Tuple[str, str, str]] = [
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# 各 GPU 的模型列表(来自 filter_verified_models 脚本的筛选结果)
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# ══════════════════════════════════════════════════════════
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METAX_MODELS = [
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"smalltotal/Flux_wx_dust",
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"fpadovani/eng-latn-10mb-after-ppt-Dp-10mb-ckpt500_seed10",
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"kandivault/sprocket-500m",
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"fpadovani/eng-latn-10mb-100mb_seed10",
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"ymh1981/unsloth_qwen2.5_3b_grpo_google_colab_f16",
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"stabilityai/stable-diffusion-2-1",
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"metercai/SimpleSDXL2",
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"AI-ModelScope/controlnet-depth-sdxl-1.0",
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"AIDC-AI/Ovis1.6-Gemma2-27B",
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"AI-ModelScope/t2i-adapter-depth-zoe-sdxl-1.0",
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"AI-ModelScope/controlnet-canny-sdxl-1.0-mid",
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"AI-ModelScope/controlnet-zoe-depth-sdxl-1.0",
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"TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill",
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"marioparreno/text-to-emoji-finetuned",
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"hbfreed/Olmo-2-1B-Distilled",
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"licyks/flux-model",
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"DiffSynth-Studio/FLUX.1-Kontext-dev-lora-ArtAug",
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"theprint/ReWiz-Qwen-2.5-14B",
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"vanta-research/atom-27b",
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"EasierAI/Qwen-2.5-32B",
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"y22ma/Qwen3-14B-finetune",
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"YouCountry/gemma-3-27b",
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"richardyoung/uigen-x-30b-moe",
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"UbiquantAI/Fleming-R1-32B",
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"cortexso/deepseek-r1-distill-qwen-14b",
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"OpenBuddy/openbuddy-yi1.5-34b-v21.6-32k-fp16",
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"OpenSeeker/OpenSeeker-v1-30B-SFT",
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"Qwen/Qwen1.5-32B",
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]
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KUNLUNXIN_MODELS = [
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"fpadovani/eng-latn-10mb-after-ppt-Dp-10mb-ckpt500_seed10",
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"kandivault/sprocket-500m",
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"fpadovani/eng-latn-10mb-100mb_seed10",
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"ymh1981/unsloth_qwen2.5_3b_grpo_google_colab_f16",
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"fpadovani/ita-latn-10mb-after-ppt-Dp-100mb-ckpt500_seed3407",
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"Qwen/Qwen3.8-27B",
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"llm-semantic-router/aegis-embed",
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]
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BIREN_MODELS = [
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"kandivault/sprocket-500m",
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"arvindcr4/iolai-2026-qwen25-14b-awq",
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"AIDC-AI/Ovis1.6-Gemma2-27B",
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"TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill",
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"marioparreno/text-to-emoji-finetuned",
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"hbfreed/Olmo-2-1B-Distilled",
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"Qwen/Qwen3.8-27B",
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"theprint/ReWiz-Qwen-2.5-14B",
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"vanta-research/atom-27b",
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"EasierAI/Qwen-2.5-32B",
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"yoriis/Gemma-Rand-CPT-IT-0.3",
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"YouCountry/gemma-3-27b",
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"richardyoung/uigen-x-30b-moe",
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"cortexso/gemma2",
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"5inq/Joi-Qwen3-14B",
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"LLM-Research/Phi-3-medium-128k-instruct",
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"UbiquantAI/Fleming-R1-32B",
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"cortexso/deepseek-r1-distill-qwen-14b",
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"OpenBuddy/openbuddy-yi1.5-34b-v21.6-32k-fp16",
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]
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CAMBRICON_MODELS = [
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"fpadovani/eng-latn-10mb-after-ppt-Dp-10mb-ckpt500_seed10",
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"kandivault/sprocket-500m",
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"fpadovani/eng-latn-10mb-100mb_seed10",
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"ymh1981/unsloth_qwen2.5_3b_grpo_google_colab_f16",
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"arvindcr4/iolai-2026-qwen25-14b-awq",
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"AIDC-AI/Ovis1.6-Gemma2-27B",
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"AIDC-AI/Ovis2-8B",
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"Qwen/Qwen3.8-27B",
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"llm-semantic-router/aegis-embed",
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"Lamapi/next-12b",
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"Kwai-Keye/Keye-VL-1_5-8B",
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]
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HYGON_MODELS = [
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"fpadovani/eng-latn-10mb-after-ppt-Dp-10mb-ckpt500_seed10",
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"fpadovani/eng-latn-10mb-100mb_seed10",
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"jerchenxin/qwen2.5-Math-1.5B-grpo_clip-full-step_0000020",
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"Papajams/ratiocine",
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"arvindcr4/iolai-2026-qwen25-14b-awq",
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"AIDC-AI/Ovis1.6-Gemma2-27B",
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"Qwen/Qwen3.8-27B",
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"kmseong/safety-warp-Llama-3.2-3b-phase3-per-layer",
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"flyingfishinwater/good_and_small_models",
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"kmseong/safety-warp-Llama-3.2-3b-phase3-no_rotation-per-layer2",
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"kmseong/safety-warp-Llama-3.2-3b-instruct-phase3-perlayer-metamath",
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"llm-semantic-router/aegis-embed",
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"moonshotai/Kimi-K2.5",
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"alibayram/magibu-128k-trained",
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"UsefulSensors/moonshine-tiny-vi",
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"XCurOS/XCurOS-1.2-8B-VLBF16-Instruct",
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"UsefulSensors/moonshine-tiny-ko",
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"UsefulSensors/moonshine-tiny-ar",
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"UsefulSensors/moonshine-tiny-ja",
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"UsefulSensors/moonshine-base-ko",
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"UsefulSensors/moonshine-base-ja",
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"Lamapi/next-12b",
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"Lamapi/next-4b",
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"kmseong/Llama-3.2-3B-gsm8k_ft_after-rsn-tuned-freeze_rsn_10",
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"UsefulSensors/moonshine-base-ar",
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"OX-PIXL/SpatialThinker-3B",
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"Kwai-Keye/Keye-VL-1_5-8B",
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"zai-org/glm-4v-9b",
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]
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MTHREADS_MODELS = [
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@@ -655,10 +716,10 @@ PPU_MODELS = [
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"espressovi/BODHI-qwen-3-maze-8b-distil",
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]
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# 本轮提交第二十八轮过滤结果:MetaX_c-500(5) / Kunlunxin_p-800(4) / hygon_k100-ai(2) /
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# Cambricon_mlu-370-x8(4) / Biren_166m(1),共16个;沿用多账号 fallback 轮转。
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# 候选池已回升到6053个(上轮仅3046),但产出仍只有16个,说明新加入的模型大多
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# 在这几张卡上已跑过;需灌入这些卡未跑过的新模型才会有更多产出。
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# 本轮提交第三十轮过滤结果:MetaX_c-500(23) / Kunlunxin_p-800(3) / hygon_k100-ai(26) /
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# Cambricon_mlu-370-x8(7) / Biren_166m(18),共77个;沿用多账号 fallback 轮转。
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# 源 model_ids 有226个重复条目,传导到txt里5个重复,灌入时已按模型ID去重
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#(txt 共82行 → 去重后77个)。
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# 本轮不提交 Mthreads_s4000(保留既有列表)/ ppu_zw_810e(机制B无白名单权限)/
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# Sunrise_pt-200-x1(v1.0.13已完成)/
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# Iluvatar_bi-150(本轮筛选为0;且本仓库 framework=vllm,现有 iluvatar 镜像均为 llamacpp/GGUF,缺 vllm 版镜像)
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