45 lines
2.4 KiB
Docker
45 lines
2.4 KiB
Docker
# enginex-bi100-compat
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#
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# 天数智芯 天垓100(Iluvatar_bi-100)· 文本生成 · vLLM「兼容增强」引擎。
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#
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# 不动模型、不动卡,只把「引擎镜像层」的结构性不兼容在启动前修掉。
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# 结构与社区已上线引擎 EngineX-Sunrise/enginex-S2-vllm-fix-tokenizer 完全同型
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# (Dockerfile + entrypoint.sh + 修补脚本 + README),该模式已在曦望 S2 生产验证。
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#
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# 修什么(全部有日志实证,见 README.md):
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# R3 extra_special_tokens 是 list -> transformers 崩(社区已上线修复,已合并)
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# R3b tokenizer_class 是坏类名 -> 加载异常(社区已上线修复,已合并)
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# R2 模型没有 chat_template -> /v1/chat/completions 400/空输出
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# R4 architectures 是镜像未注册类名 -> KeyError / MODEL_NOT_SUPPORTED
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# R7 镜像缺 ixformer.contrib.vllm.layers -> ModuleNotFoundError(MoE)
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#
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# 为什么选 bi-100:本人 37 个验证失败里,bi-100 单卡 10 例为全平台最集中;
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# 且该卡社区通过率约 51%(15 张卡最低),修好收益最大。
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FROM git.modelhub.org.cn:9443/enginex-iluvatar/bi100-3.2.3-x86-ubuntu20.04-py3.10-poc-llm-infer:v1.2.3
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LABEL org.opencontainers.image.title="enginex-bi100-compat" \
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org.opencontainers.image.description="Iluvatar bi-100 vLLM text-generation engine with preflight compatibility patches (R2/R3/R3b/R4/R7)" \
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com.modelhubxc.engine.target-card="Iluvatar_bi-100" \
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com.modelhubxc.engine.framework="vllm" \
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com.modelhubxc.engine.task-type="text-generation" \
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com.modelhubxc.engine.baseline="EngineX-Iluvatar/enginex-vllm-bi100-qwen36" \
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com.modelhubxc.engine.pattern="EngineX-Sunrise/enginex-S2-vllm-fix-tokenizer"
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# 修补脚本 + R7 纯 PyTorch shim(都只是小文本文件,无权重)
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COPY preflight.py /opt/
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COPY entrypoint.sh /opt/
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COPY detect_tokenizer.py /opt/
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COPY shims/ /opt/shims/
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RUN chmod +x /opt/entrypoint.sh /opt/preflight.py \
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&& python3 -c "import ast,io;[ast.parse(io.open(f,encoding='utf-8').read()) for f in ['/opt/preflight.py','/opt/detect_tokenizer.py','/opt/shims/ixformer/contrib/vllm/layers/__init__.py']]" \
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&& bash -n /opt/entrypoint.sh \
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&& echo "[enginex-bi100-compat] preflight syntax OK"
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# R7:让 shims 全局可 import(平台若覆盖 entrypoint 也仍然生效)
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ENV PYTHONPATH=/opt/shims:${PYTHONPATH}
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ENV MODEL_DIR=/model
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ENTRYPOINT ["/opt/entrypoint.sh"]
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