镜像构建历史
# 2026-10-27 06:55:38 0.00B 设置默认要执行的命令
CMD ["/usr/local/bin/unsloth-studio-launch"]
# 2026-10-27 06:55:38 0.00B 执行命令并创建新的镜像层
RUN |4 UNSLOTH_STUDIO_REF=0ea04730dbcac3d5cea8440992c0454a0e0fb4ae UNSLOTH_STUDIO_ZOO_REF=631b5e878ff1fbd89819491b8ee0b36e9356af1f LLAMA_PREBUILT_TAG=b11876-mix-ec42614 TARGETARCH=amd64 /bin/sh -c chmod +x /usr/local/bin/unsloth-entrypoint # buildkit
# 2026-10-27 06:55:38 9.68KB 复制新文件或目录到容器中
COPY entrypoint.sh /usr/local/bin/unsloth-entrypoint # buildkit
# 2026-10-27 06:55:38 0.00B 声明容器运行时监听的端口
EXPOSE [22/tcp 8000/tcp 8888/tcp]
# 2026-10-27 06:55:38 12.45KB 执行命令并创建新的镜像层
RUN |4 UNSLOTH_STUDIO_REF=0ea04730dbcac3d5cea8440992c0454a0e0fb4ae UNSLOTH_STUDIO_ZOO_REF=631b5e878ff1fbd89819491b8ee0b36e9356af1f LLAMA_PREBUILT_TAG=b11876-mix-ec42614 TARGETARCH=amd64 /bin/sh -c chmod +x /usr/local/bin/unsloth-studio-home /usr/local/bin/unsloth-studio-launch /usr/local/bin/unsloth-studio-password /usr/local/bin/unsloth-studio-run /usr/local/bin/unsloth-studio-update /usr/local/bin/unsloth-llama-update /usr/local/bin/unsloth-jupyter-tunnel # buildkit
# 2026-10-27 06:55:38 43.68KB 执行命令并创建新的镜像层
RUN |4 UNSLOTH_STUDIO_REF=0ea04730dbcac3d5cea8440992c0454a0e0fb4ae UNSLOTH_STUDIO_ZOO_REF=631b5e878ff1fbd89819491b8ee0b36e9356af1f LLAMA_PREBUILT_TAG=b11876-mix-ec42614 TARGETARCH=amd64 /bin/sh -c SP="$(/opt/unsloth-venv/bin/python -c 'import sysconfig; print(sysconfig.get_path("purelib"))')" && cp /tmp/unsloth-branding-guard/unsloth_branding.py "${SP}/unsloth_branding.py" && mkdir -p /opt/unsloth-venv/etc/jupyter/jupyter_server_config.d && cp /tmp/unsloth-branding-guard/unsloth_branding_guard.json /opt/unsloth-venv/etc/jupyter/jupyter_server_config.d/unsloth_branding_guard.json && cp "${UNSLOTH_STUDIO_HOME}/src/studio/LICENSE.AGPL-3.0" /opt/unsloth-venv/share/jupyter/UNSLOTH_LICENSE.AGPL-3.0 && rm -rf /tmp/unsloth-branding-guard && /opt/unsloth-venv/bin/python -m unsloth_branding --verify # buildkit
# 2026-10-27 06:55:38 91.00B 复制新文件或目录到容器中
COPY jupyter/jupyter_server_config.d/unsloth_branding_guard.json /tmp/unsloth-branding-guard/unsloth_branding_guard.json # buildkit
# 2026-10-27 06:55:38 9.06KB 复制新文件或目录到容器中
COPY jupyter/unsloth_branding.py /tmp/unsloth-branding-guard/unsloth_branding.py # buildkit
# 2026-10-27 06:55:38 3.41MB 执行命令并创建新的镜像层
RUN |4 UNSLOTH_STUDIO_REF=0ea04730dbcac3d5cea8440992c0454a0e0fb4ae UNSLOTH_STUDIO_ZOO_REF=631b5e878ff1fbd89819491b8ee0b36e9356af1f LLAMA_PREBUILT_TAG=b11876-mix-ec42614 TARGETARCH=amd64 /bin/sh -c JS="$(/opt/unsloth-venv/bin/python -c 'import os, jupyter_server; print(os.path.dirname(jupyter_server.__file__))')" && for n in favicon.ico favicon-notebook.ico favicon-file.ico favicon-terminal.ico; do cp /tmp/unsloth-branding/favicon.ico "${JS}/static/favicons/${n}"; done && cp /tmp/unsloth-branding/logo.png "${JS}/static/logo/logo.png" && cp /tmp/unsloth-branding/login.html "${JS}/templates/login.html" && { /opt/unsloth-venv/bin/python /tmp/unsloth-branding/install_sloth_stickers.py --src "${UNSLOTH_STUDIO_HOME}/src/studio/frontend/public/Sloth emojis" --dest "${JS}/static/sloth" || echo ">> sloth stickers not installed (login falls back to the Unsloth logo)"; } && rm -rf /tmp/unsloth-branding && /opt/unsloth-venv/bin/jupyter labextension disable @jupyterlab/application-extension:logo && /opt/unsloth-venv/bin/jupyter labextension lock @jupyterlab/application-extension:logo && /opt/unsloth-venv/bin/jupyter labextension disable @jupyterlab/apputils-extension:splash && /opt/unsloth-venv/bin/jupyter labextension lock @jupyterlab/apputils-extension:splash && /opt/unsloth-venv/bin/jupyter labextension lock unsloth-jupyterlab # buildkit
# 2026-10-27 06:55:26 2.39KB 复制新文件或目录到容器中
COPY jupyter/install_sloth_stickers.py /tmp/unsloth-branding/install_sloth_stickers.py # buildkit
# 2026-10-27 06:55:26 5.09KB 复制新文件或目录到容器中
COPY jupyter/login.html /tmp/unsloth-branding/login.html # buildkit
# 2026-10-27 06:55:26 14.42KB 复制新文件或目录到容器中
COPY jupyter/logo.png /tmp/unsloth-branding/logo.png # buildkit
# 2026-10-27 06:55:26 16.90KB 复制新文件或目录到容器中
COPY jupyter/favicon.ico /tmp/unsloth-branding/favicon.ico # buildkit
# 2026-10-27 06:55:26 89.76KB 复制新文件或目录到容器中
COPY /opt/labext-src/unsloth-jupyterlab/labextension /opt/unsloth-venv/share/jupyter/labextensions/unsloth-jupyterlab # buildkit
# 2026-10-27 06:55:26 968.00B 复制新文件或目录到容器中
COPY jupyter/overrides.json /opt/unsloth-venv/share/jupyter/lab/settings/overrides.json # buildkit
# 2026-10-27 06:55:26 2.25KB 复制新文件或目录到容器中
COPY unsloth_jupyter_tunnel.sh /usr/local/bin/unsloth-jupyter-tunnel # buildkit
# 2026-10-27 06:55:26 9.40KB 复制新文件或目录到容器中
COPY fetch_llama_prebuilt.py /usr/local/lib/unsloth/fetch_llama_prebuilt.py # buildkit
# 2026-10-27 06:55:26 8.45KB 复制新文件或目录到容器中
COPY unsloth_llama_update.sh /usr/local/bin/unsloth-llama-update # buildkit
# 2026-10-27 06:55:26 27.95KB 复制新文件或目录到容器中
COPY unsloth_studio_update.sh /usr/local/bin/unsloth-studio-update # buildkit
# 2026-10-27 06:55:26 3.94KB 复制新文件或目录到容器中
COPY studio_run.sh /usr/local/bin/unsloth-studio-run # buildkit
# 2026-10-27 06:55:26 5.12KB 复制新文件或目录到容器中
COPY studio_password.sh /usr/local/bin/unsloth-studio-password # buildkit
# 2026-10-27 06:55:26 8.51KB 复制新文件或目录到容器中
COPY studio_launch.sh /usr/local/bin/unsloth-studio-launch # buildkit
# 2026-10-27 06:55:26 3.13KB 复制新文件或目录到容器中
COPY supervisord.conf /etc/supervisor/supervisord.conf # buildkit
# 2026-10-27 06:55:25 5.79GB 执行命令并创建新的镜像层
RUN |4 UNSLOTH_STUDIO_REF=0ea04730dbcac3d5cea8440992c0454a0e0fb4ae UNSLOTH_STUDIO_ZOO_REF=631b5e878ff1fbd89819491b8ee0b36e9356af1f LLAMA_PREBUILT_TAG=b11876-mix-ec42614 TARGETARCH=amd64 /bin/sh -c set -eux && case "${TARGETARCH:-amd64}" in amd64) TORCH_FAMILY="cu128"; AUDIO_CPP_ACCELERATOR="cuda" ;; arm64) TORCH_FAMILY="cu128"; AUDIO_CPP_ACCELERATOR="auto" ;; *) echo "ERROR: unsupported TARGETARCH=${TARGETARCH}" >&2; exit 1 ;; esac && mkdir -p "${UNSLOTH_STUDIO_HOME}" && ln -s /opt/unsloth/llama.cpp "${UNSLOTH_STUDIO_HOME}/llama.cpp" && touch /opt/unsloth/llama.cpp/.unsloth-studio-owned && git init -q "${UNSLOTH_STUDIO_HOME}/src" && cd "${UNSLOTH_STUDIO_HOME}/src" && git remote add origin https://github.com/unslothai/unsloth && git fetch -q --depth 1 origin "${UNSLOTH_STUDIO_REF}" && git checkout -q FETCH_HEAD && UNSLOTH_STUDIO_HOME="${UNSLOTH_STUDIO_HOME}" UNSLOTH_TORCH_INDEX_FAMILY="${TORCH_FAMILY}" UNSLOTH_ZOO_REF="${UNSLOTH_STUDIO_ZOO_REF}" UNSLOTH_LLAMA_TAG="${LLAMA_PREBUILT_TAG}" UNSLOTH_LLAMA_KEEP_PREBUILT=1 UNSLOTH_AUDIO_CPP_ACCELERATOR="${AUDIO_CPP_ACCELERATOR}" UNSLOTH_PYTHON=3.12 UNSLOTH_ALLOW_CPU=1 bash install.sh --local && BASE_TORCH="$(/opt/unsloth-venv/bin/python -c "from importlib.metadata import version; print(version('torch'))")" && "${UNSLOTH_STUDIO_HOME}/unsloth_studio/bin/python" -c "import sys; from importlib.metadata import version; assert sys.version_info[:2] == (3, 12), 'Unsloth Studio venv python %d.%d is not 3.12 (UNSLOTH_PYTHON pin ignored) -- CUDA dedup below depends on it' % sys.version_info[:2]; v = version('torch'); assert v == '${BASE_TORCH}', 'Unsloth Studio venv torch ' + v + ' does not match base venv torch ${BASE_TORCH} (CUDA dedup would link mismatched libs)'; print('Unsloth Studio venv python %d.%d torch' % sys.version_info[:2], v, '== base', '${BASE_TORCH}')" && { "${UNSLOTH_STUDIO_HOME}/llama.cpp/llama-quantize" --help 2>&1 || true; } | grep -q "usage" && for CUDA_SO in /opt/unsloth/llama.cpp/libggml-cuda.so /opt/unsloth/llama.cpp/build/bin/libggml-cuda.so; do [ -f "$CUDA_SO" ] || { echo "ERROR: $CUDA_SO is missing after install.sh; GGUF inference would silently run on the CPU"; cat /opt/unsloth/llama.cpp/UNSLOTH_PREBUILT_INFO.json || true; exit 1; }; done && echo "OK: Unsloth Studio kept the base image's CUDA llama.cpp bundle" && rm -rf "${UNSLOTH_STUDIO_HOME}/src/.git" "${UNSLOTH_STUDIO_HOME}/src/studio/frontend/node_modules" "${UV_CACHE_DIR:-${UNSLOTH_STUDIO_HOME}/cache/uv}" /root/.cache && for NVRTC_DIR in "${UNSLOTH_STUDIO_HOME}"/unsloth_studio/lib/python*/site-packages/nvidia/cuda_nvrtc/lib; do if [ -f "${NVRTC_DIR}/libnvrtc.so.12" ] && [ ! -L "${NVRTC_DIR}/libnvrtc.so.12" ]; then mv "${NVRTC_DIR}/libnvrtc.so.12" "${NVRTC_DIR}/libnvrtc.so.12.cu128.orig"; ln -s libnvrtc.so.12.cu128.orig "${NVRTC_DIR}/libnvrtc.so.12"; ln -s /usr/local/cuda-13.0/lib64/libnvrtc.so.13 "${NVRTC_DIR}/libnvrtc.so.12.cu13"; fi; done && BASE_NV=/opt/unsloth-venv/lib/python3.12/site-packages/nvidia && STU_NV="${UNSLOTH_STUDIO_HOME}/unsloth_studio/lib/python3.12/site-packages/nvidia" && if [ ! -d "${STU_NV}" ] || [ ! -d "${BASE_NV}" ]; then echo ">> nvidia dir missing (STU=${STU_NV} BASE=${BASE_NV}); skipping CUDA dedup"; else find "${UNSLOTH_STUDIO_HOME}/unsloth_studio" -name '*.a' -delete; rm -f "${STU_NV}/nvshmem/lib/libnvshmem_device.bc"; for c in cudnn cublas cusparselt nccl cusolver cusparse cufft curand nvjitlink cuda_cupti nvshmem npp; do b="${BASE_NV}/${c}/lib"; s="${STU_NV}/${c}/lib"; { [ -d "$b" ] && [ -d "$s" ]; } || { echo ">> skip ${c} (dir missing)"; continue; }; if [ "${c}" = "npp" ]; then rm -rf "$s" && ln -s "$b" "$s" && readlink -e "$s" >/dev/null; echo ">> deduped npp -> base (pruned)"; elif [ "$(cd "$s" && ls | sort | tr '\n' ' ')" = "$(cd "$b" && ls | sort | tr '\n' ' ')" ]; then rm -rf "$s" && ln -s "$b" "$s" && readlink -e "$s" >/dev/null; echo ">> deduped ${c} -> base"; else echo ">> skip ${c} (file set differs base vs studio)"; fi; done; echo "studio venv size after dedup:"; du -sh "${UNSLOTH_STUDIO_HOME}/unsloth_studio"; fi && mkdir -p "${UNSLOTH_STUDIO_APP}" && find "${UNSLOTH_STUDIO_HOME}" -mindepth 1 -maxdepth 1 ! -name cache -exec mv -t "${UNSLOTH_STUDIO_APP}" {} + && test ! -e "${UNSLOTH_STUDIO_HOME}/cache/uv" && bash /usr/local/bin/unsloth-studio-home && "${UNSLOTH_STUDIO_HOME}/unsloth_studio/bin/python" -c "import os, sys, studio; print('Unsloth Studio venv', sys.prefix, 'imports studio from', studio.__file__); assert os.path.realpath(studio.__file__).startswith(os.path.realpath('${UNSLOTH_STUDIO_HOME}/src') + '/'), studio.__file__" && ls -la "${UNSLOTH_STUDIO_HOME}" # buildkit
# 2026-10-27 06:52:37 9.41KB 复制新文件或目录到容器中
COPY studio_home.sh /usr/local/bin/unsloth-studio-home # buildkit
# 2026-10-27 06:52:37 13.08MB 执行命令并创建新的镜像层
RUN |4 UNSLOTH_STUDIO_REF=0ea04730dbcac3d5cea8440992c0454a0e0fb4ae UNSLOTH_STUDIO_ZOO_REF=631b5e878ff1fbd89819491b8ee0b36e9356af1f LLAMA_PREBUILT_TAG=b11876-mix-ec42614 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends curl git ca-certificates supervisor openssh-server && rm -rf /var/lib/apt/lists/* # buildkit
# 2026-10-27 06:52:37 0.00B 设置环境变量 UNSLOTH_STUDIO_HOME UNSLOTH_STUDIO_APP UNSLOTH_STUDIO_DOCUMENTS_HOME UNSLOTH_STUDIO_SKILLS_HOME UV_CACHE_DIR UNSLOTH_IMAGE_ALLOW_CPU JUPYTER_PORT UNSLOTH_STUDIO_PORT UNSLOTH_ENABLE_SSHD UNSLOTH_STUDIO_SHUTDOWN_STOP_TIMEOUT_S UNSLOTH_STUDIO_STOP_WAIT_S DEBIAN_FRONTEND
ENV UNSLOTH_STUDIO_HOME=/opt/unsloth-studio UNSLOTH_STUDIO_APP=/opt/unsloth-studio-app UNSLOTH_STUDIO_DOCUMENTS_HOME=/opt/unsloth-studio/documents UNSLOTH_STUDIO_SKILLS_HOME=/opt/unsloth-studio/skills UV_CACHE_DIR=/opt/unsloth-studio-app/uv-cache UNSLOTH_IMAGE_ALLOW_CPU=1 JUPYTER_PORT=8888 UNSLOTH_STUDIO_PORT=8000 UNSLOTH_ENABLE_SSHD=false UNSLOTH_STUDIO_SHUTDOWN_STOP_TIMEOUT_S=120 UNSLOTH_STUDIO_STOP_WAIT_S=150 DEBIAN_FRONTEND=noninteractive
# 2026-10-27 06:52:37 0.00B 指定运行容器时使用的用户
USER root
# 2026-10-27 06:52:37 0.00B 定义构建参数
ARG TARGETARCH=amd64
# 2026-10-27 06:52:37 0.00B 定义构建参数
ARG LLAMA_PREBUILT_TAG=b11876-mix-ec42614
# 2026-10-27 06:52:37 0.00B 定义构建参数
ARG UNSLOTH_STUDIO_ZOO_REF=631b5e878ff1fbd89819491b8ee0b36e9356af1f
# 2026-10-27 06:52:37 0.00B 定义构建参数
ARG UNSLOTH_STUDIO_REF=0ea04730dbcac3d5cea8440992c0454a0e0fb4ae
# 2026-10-27 04:42:52 0.00B 设置默认要执行的命令
CMD ["python"]
# 2026-10-27 04:42:52 0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/usr/local/bin/unsloth-entrypoint"]
# 2026-10-27 04:42:52 0.00B 执行命令并创建新的镜像层
RUN |5 TARGETARCH=amd64 PYTHON_VERSION=3.12 CUDA_VERSION=12.8.1 LLAMA_PREBUILT_TAG=b11876-mix-ec42614 UNSLOTH_NOTEBOOKS_REF=c55d0eccc722a7754036a447bdd5cd83499d4350 /bin/sh -c chmod +x /usr/local/bin/unsloth-entrypoint # buildkit
# 2026-10-27 04:42:52 9.68KB 复制新文件或目录到容器中
COPY entrypoint.sh /usr/local/bin/unsloth-entrypoint # buildkit
# 2026-10-27 04:42:52 4.69KB 复制新文件或目录到容器中
COPY smoke_test.py /workspace/smoke_test.py # buildkit
# 2026-10-27 04:42:52 0.00B 声明容器运行时监听的端口
EXPOSE map[8888/tcp:{}]
# 2026-10-27 04:42:52 211.32MB 执行命令并创建新的镜像层
RUN |5 TARGETARCH=amd64 PYTHON_VERSION=3.12 CUDA_VERSION=12.8.1 LLAMA_PREBUILT_TAG=b11876-mix-ec42614 UNSLOTH_NOTEBOOKS_REF=c55d0eccc722a7754036a447bdd5cd83499d4350 /bin/sh -c set -eux && git init -q /opt/unsloth-notebooks && git -C /opt/unsloth-notebooks remote add origin https://github.com/unslothai/notebooks && git -C /opt/unsloth-notebooks fetch -q --depth 1 origin "${UNSLOTH_NOTEBOOKS_REF}" && git -C /opt/unsloth-notebooks checkout -q FETCH_HEAD && git -C /opt/unsloth-notebooks rev-parse HEAD > /opt/unsloth-notebooks/.unsloth_template_commit && rm -rf /opt/unsloth-notebooks/.git && du -sh /opt/unsloth-notebooks # buildkit
# 2026-10-27 04:42:43 0.00B 定义构建参数
ARG UNSLOTH_NOTEBOOKS_REF=main
# 2026-10-27 04:42:43 0.00B 设置环境变量 IPYTHONDIR
ENV IPYTHONDIR=/opt/unsloth-nb/ipython
# 2026-10-27 04:42:43 0.00B 设置环境变量 PATH
ENV PATH=/opt/unsloth-nb/bin:/opt/unsloth-venv/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
# 2026-10-27 04:42:43 135.89KB 执行命令并创建新的镜像层
RUN |4 TARGETARCH=amd64 PYTHON_VERSION=3.12 CUDA_VERSION=12.8.1 LLAMA_PREBUILT_TAG=b11876-mix-ec42614 /bin/sh -c set -eux && SP=/opt/unsloth-venv/lib/python${PYTHON_VERSION}/site-packages && cp /opt/unsloth-nb/unsloth_nb_compat.py "$SP/unsloth_nb_compat.py" && cp /opt/unsloth-nb/unsloth_nb_pip_magic.py "$SP/unsloth_nb_pip_magic.py" && cp /opt/unsloth-nb/unsloth_colab_compat.py "$SP/unsloth_colab_compat.py" && chmod +x /opt/unsloth-nb/unsloth_pip_shim.py /opt/unsloth-nb/unsloth_root_shim.py /opt/unsloth-nb/unsloth_run.py /opt/unsloth-nb/unsloth_sync_notebooks.sh /opt/unsloth-nb/unsloth_nb_content_sig.py /opt/unsloth-nb/unsloth_nb_view.py /opt/unsloth-nb/unsloth_nb_strip_colab.py && mkdir -p /opt/unsloth-nb/bin && for t in pip pip3 uv; do ln -sf /opt/unsloth-nb/unsloth_pip_shim.py /opt/unsloth-nb/bin/$t; done && for t in apt apt-get dpkg sudo; do ln -sf /opt/unsloth-nb/unsloth_root_shim.py /opt/unsloth-nb/bin/$t; done && ln -sf /opt/unsloth-nb/unsloth_run.py /usr/local/bin/unsloth-run && ln -sf /opt/unsloth-nb/unsloth_sync_notebooks.sh /usr/local/bin/unsloth-sync-notebooks && ln -sf /opt/unsloth-nb/unsloth_nb_content_sig.py /usr/local/bin/unsloth-nb-content-sig && ln -sf /opt/unsloth-nb/unsloth_nb_view.py /usr/local/bin/unsloth-nb-view && ln -sf /opt/unsloth-nb/unsloth_nb_strip_colab.py /usr/local/bin/unsloth-nb-strip-colab && mkdir -p /opt/unsloth-nb/ipython/profile_default/startup && cp /opt/unsloth-nb/unsloth_ipython_startup.py /opt/unsloth-nb/ipython/profile_default/startup/00-unsloth-nb.py && chmod -R a+rX /opt/unsloth-nb/ipython && chmod 1777 /opt/unsloth-nb/ipython /opt/unsloth-nb/ipython/profile_default && /opt/unsloth-venv/bin/python -c "import sys, glob; sys.path.insert(0, '$SP'); import unsloth_nb_compat, unsloth_colab_compat; print('nb-compat OK; baked sidecars:', sorted(glob.glob('/opt/unsloth-venv/tf-sidecars/t_*')))" && /opt/unsloth-venv/bin/python /opt/unsloth-nb/unsloth_pip_shim.py --unsloth-selfcheck-value-flags # buildkit
# 2026-10-27 04:42:42 135.45KB 复制新文件或目录到容器中
COPY unsloth_nb_compat.py unsloth_pip_shim.py unsloth_root_shim.py unsloth_nb_pip_magic.py unsloth_ipython_startup.py unsloth_run.py unsloth_sync_notebooks.sh unsloth_nb_content_sig.py unsloth_nb_view.py unsloth_nb_strip_colab.py unsloth_colab_compat.py /opt/unsloth-nb/ # buildkit
# 2026-10-27 04:42:42 0.00B 执行命令并创建新的镜像层
RUN |4 TARGETARCH=amd64 PYTHON_VERSION=3.12 CUDA_VERSION=12.8.1 LLAMA_PREBUILT_TAG=b11876-mix-ec42614 /bin/sh -c mkdir -p ${HF_HOME} ${TRITON_CACHE_DIR} && chmod -R a+rwX /workspace # buildkit
# 2026-10-27 04:42:42 0.00B 设置工作目录为/workspace
WORKDIR /workspace
# 2026-10-27 04:42:42 0.00B 设置环境变量 UNSLOTH_LLAMA_CPP_PATH
ENV UNSLOTH_LLAMA_CPP_PATH=/opt/unsloth/llama.cpp
# 2026-10-27 04:42:42 0.00B 执行命令并创建新的镜像层
RUN |4 TARGETARCH=amd64 PYTHON_VERSION=3.12 CUDA_VERSION=12.8.1 LLAMA_PREBUILT_TAG=b11876-mix-ec42614 /bin/sh -c set -eux && CUDA_SO=/opt/unsloth/llama.cpp/libggml-cuda.so && if [ -f "$CUDA_SO" ]; then want="$(ldd "$CUDA_SO" | sed -n 's/^[[:space:]]*\(libcublas\.so\.[0-9]*\)[[:space:]]*=> not found$/\1/p' | head -n1)"; if [ -n "$want" ]; then major="${want##*.}"; if [ "$major" -ge 13 ]; then pkg="nvidia-cublas==${major}.*"; else pkg="nvidia-cublas-cu${major}"; fi; echo ">> $want missing, installing ${pkg}"; /opt/unsloth-venv/bin/uv pip install --python /opt/unsloth-venv/bin/python "${pkg}"; ldconfig; fi; missing="$(ldd "$CUDA_SO" | grep 'not found' | grep -v 'libcuda\.so\.1 ' || true)"; if [ -n "$missing" ]; then echo "ERROR: llama.cpp CUDA backend has unresolved libraries:"; echo "$missing"; echo "GGUF inference would silently fall back to the CPU."; exit 1; fi; echo "OK: llama.cpp CUDA backend dependencies all resolve"; else echo ">> no libggml-cuda.so in this bundle (CPU-only build)"; fi # buildkit
# 2026-10-27 04:42:42 436.33MB 执行命令并创建新的镜像层
RUN |4 TARGETARCH=amd64 PYTHON_VERSION=3.12 CUDA_VERSION=12.8.1 LLAMA_PREBUILT_TAG=b11876-mix-ec42614 /bin/sh -c /opt/unsloth-venv/bin/python /tmp/fetch_llama_prebuilt.py "${LLAMA_PREBUILT_TAG}" "${TARGETARCH:-amd64}" /opt/unsloth/llama.cpp && rm -f /tmp/fetch_llama_prebuilt.py && cat /opt/unsloth/llama.cpp/UNSLOTH_PREBUILT_INFO.json # buildkit
# 2026-10-27 04:42:35 9.40KB 复制新文件或目录到容器中
COPY fetch_llama_prebuilt.py /tmp/fetch_llama_prebuilt.py # buildkit
# 2026-10-27 04:42:35 0.00B 定义构建参数
ARG LLAMA_PREBUILT_TAG=latest
# 2026-10-27 04:42:35 52.66KB 执行命令并创建新的镜像层
RUN |3 TARGETARCH=amd64 PYTHON_VERSION=3.12 CUDA_VERSION=12.8.1 /bin/sh -c set -eux && SP=/opt/unsloth-venv/lib/python${PYTHON_VERSION}/site-packages && printf "%s\n" "$SP/torch/lib" "$SP/nvidia/cuda_nvrtc/lib" "$SP/nvidia/cuda_runtime/lib" "$SP/nvidia/npp/lib" "$SP/nvidia/cublas/lib" "$SP/nvidia/cu13/lib" > /etc/ld.so.conf.d/zz-unsloth-venv.conf && ldconfig && { /opt/unsloth-venv/bin/python -c "import torchcodec; print('torchcodec', torchcodec.__version__)" || echo ">> torchcodec unavailable on this arch (audio decode falls back)"; } # buildkit
# 2026-10-27 04:42:29 703.09MB 执行命令并创建新的镜像层
RUN |3 TARGETARCH=amd64 PYTHON_VERSION=3.12 CUDA_VERSION=12.8.1 /bin/sh -c set -eux; apt-get update; apt-get install -y --no-install-recommends cuda-nvrtc-13-0 cuda-nvcc-13-0; update-alternatives --set cuda /usr/local/cuda-12.8; rm -rf /var/lib/apt/lists/*; NVRTC_DIR=/opt/unsloth-venv/lib/python${PYTHON_VERSION}/site-packages/nvidia/cuda_nvrtc/lib; if [ -f "${NVRTC_DIR}/libnvrtc.so.12" ] && [ ! -L "${NVRTC_DIR}/libnvrtc.so.12" ]; then mv "${NVRTC_DIR}/libnvrtc.so.12" "${NVRTC_DIR}/libnvrtc.so.12.cu128.orig"; ln -s libnvrtc.so.12.cu128.orig "${NVRTC_DIR}/libnvrtc.so.12"; ln -s /usr/local/cuda-13.0/lib64/libnvrtc.so.13 "${NVRTC_DIR}/libnvrtc.so.12.cu13"; fi # buildkit
# 2026-10-27 04:42:11 12.94GB 复制新文件或目录到容器中
COPY /opt/unsloth-venv /opt/unsloth-venv # buildkit
# 2026-10-27 04:36:03 1.27GB 执行命令并创建新的镜像层
RUN |3 TARGETARCH=amd64 PYTHON_VERSION=3.12 CUDA_VERSION=12.8.1 /bin/sh -c CUDA_PKG="$(echo "${CUDA_VERSION}" | awk -F. '{print $1"-"$2}')" && apt-get update && apt-get install -y --no-install-recommends software-properties-common ca-certificates curl wget git libgomp1 gcc g++ zstd ffmpeg ninja-build "cuda-nvcc-${CUDA_PKG}" "cuda-cudart-dev-${CUDA_PKG}" && for i in 1 2 3 4 5; do add-apt-repository -y ppa:deadsnakes/ppa && break; [ "$i" = 5 ] && exit 1; echo "add-apt-repository failed (attempt $i), retrying in 30s"; sleep 30; done && apt-get update && apt-get install -y --no-install-recommends python${PYTHON_VERSION} python${PYTHON_VERSION}-venv python${PYTHON_VERSION}-dev && ln -sf /usr/bin/python${PYTHON_VERSION} /usr/local/bin/python && ln -sf /usr/bin/python${PYTHON_VERSION} /usr/local/bin/python3 && test -x /usr/local/cuda/bin/nvcc && rm -rf /var/lib/apt/lists/* # buildkit
# 2026-10-27 04:36:03 0.00B 设置环境变量 DEBIAN_FRONTEND PIP_NO_CACHE_DIR PYTHONDONTWRITEBYTECODE PYTHONUNBUFFERED PATH HF_HOME TRITON_CACHE_DIR TORCH_CUDA_ARCH_LIST
ENV DEBIAN_FRONTEND=noninteractive PIP_NO_CACHE_DIR=1 PYTHONDONTWRITEBYTECODE=1 PYTHONUNBUFFERED=1 PATH=/opt/unsloth-venv/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin HF_HOME=/workspace/.cache/huggingface TRITON_CACHE_DIR=/workspace/.cache/triton TORCH_CUDA_ARCH_LIST=7.5;8.0;8.6;8.9;9.0;10.0;12.0+PTX
# 2026-10-27 04:36:03 0.00B 定义构建参数
ARG CUDA_VERSION
# 2026-10-27 04:36:03 0.00B 定义构建参数
ARG PYTHON_VERSION
# 2026-10-27 04:36:03 0.00B 定义构建参数
ARG TARGETARCH
# 2025-03-11 06:19:21 0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
# 2025-03-11 06:19:21 0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
# 2025-03-11 06:19:21 17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
# 2025-03-11 06:19:21 0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/cuda/lib64
# 2025-03-11 06:19:21 0.00B 设置环境变量 PATH
ENV PATH=/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
# 2025-03-11 06:19:21 22.00B 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c echo "/usr/local/cuda/lib64" >> /etc/ld.so.conf.d/nvidia.conf # buildkit
# 2025-03-11 06:19:21 203.31MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-cudart-12-8=${NV_CUDA_CUDART_VERSION} cuda-compat-12-8 && rm -rf /var/lib/apt/lists/* # buildkit
# 2025-03-11 06:19:07 0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=12.8.1
# 2025-03-11 06:19:07 16.75MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends gnupg2 curl ca-certificates && curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2404/${NVARCH}/3bf863cc.pub | apt-key add - && echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2404/${NVARCH} /" > /etc/apt/sources.list.d/cuda.list && apt-get purge --autoremove -y curl && rm -rf /var/lib/apt/lists/* # buildkit
# 2025-03-11 06:19:07 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2025-03-11 06:19:07 0.00B 定义构建参数
ARG TARGETARCH
# 2025-03-11 06:19:07 0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=12.8.90-1
# 2025-03-11 06:19:07 0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand
ENV NVIDIA_REQUIRE_CUDA=cuda>=12.8 brand=unknown,driver>=470,driver<471 brand=grid,driver>=470,driver<471 brand=tesla,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=vapps,driver>=470,driver<471 brand=vpc,driver>=470,driver<471 brand=vcs,driver>=470,driver<471 brand=vws,driver>=470,driver<471 brand=cloudgaming,driver>=470,driver<471 brand=unknown,driver>=535,driver<536 brand=grid,driver>=535,driver<536 brand=tesla,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=vapps,driver>=535,driver<536 brand=vpc,driver>=535,driver<536 brand=vcs,driver>=535,driver<536 brand=vws,driver>=535,driver<536 brand=cloudgaming,driver>=535,driver<536 brand=unknown,driver>=550,driver<551 brand=grid,driver>=550,driver<551 brand=tesla,driver>=550,driver<551 brand=nvidia,driver>=550,driver<551 brand=quadro,driver>=550,driver<551 brand=quadrortx,driver>=550,driver<551 brand=nvidiartx,driver>=550,driver<551 brand=vapps,driver>=550,driver<551 brand=vpc,driver>=550,driver<551 brand=vcs,driver>=550,driver<551 brand=vws,driver>=550,driver<551 brand=cloudgaming,driver>=550,driver<551 brand=unknown,driver>=560,driver<561 brand=grid,driver>=560,driver<561 brand=tesla,driver>=560,driver<561 brand=nvidia,driver>=560,driver<561 brand=quadro,driver>=560,driver<561 brand=quadrortx,driver>=560,driver<561 brand=nvidiartx,driver>=560,driver<561 brand=vapps,driver>=560,driver<561 brand=vpc,driver>=560,driver<561 brand=vcs,driver>=560,driver<561 brand=vws,driver>=560,driver<561 brand=cloudgaming,driver>=560,driver<561 brand=unknown,driver>=565,driver<566 brand=grid,driver>=565,driver<566 brand=tesla,driver>=565,driver<566 brand=nvidia,driver>=565,driver<566 brand=quadro,driver>=565,driver<566 brand=quadrortx,driver>=565,driver<566 brand=nvidiartx,driver>=565,driver<566 brand=vapps,driver>=565,driver<566 brand=vpc,driver>=565,driver<566 brand=vcs,driver>=565,driver<566 brand=vws,driver>=565,driver<566 brand=cloudgaming,driver>=565,driver<566
# 2025-03-11 06:19:07 0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
# 2025-01-27 12:14:03 0.00B
/bin/sh -c #(nop) CMD ["/bin/bash"]
# 2025-01-27 12:14:03 78.13MB
/bin/sh -c #(nop) ADD file:6df775300d76441aa33f31b22c1afce8dfe35c8ffbc14ef27c27009235b12a95 in /
# 2025-01-27 12:14:00 0.00B
/bin/sh -c #(nop) LABEL org.opencontainers.image.version=24.04
# 2025-01-27 12:14:00 0.00B
/bin/sh -c #(nop) LABEL org.opencontainers.image.ref.name=ubuntu
# 2025-01-27 12:14:00 0.00B
/bin/sh -c #(nop) ARG LAUNCHPAD_BUILD_ARCH
# 2025-01-27 12:14:00 0.00B
/bin/sh -c #(nop) ARG RELEASE
镜像信息
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"Parent": "",
"Comment": "buildkit.dockerfile.v0",
"Created": "2026-10-26T22:55:38.421236198Z",
"Container": "",
"ContainerConfig": null,
"DockerVersion": "",
"Author": "",
"Config": {
"Hostname": "",
"Domainname": "",
"User": "root",
"AttachStdin": false,
"AttachStdout": false,
"AttachStderr": false,
"ExposedPorts": {
"22/tcp": {},
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"8888/tcp": {}
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"Env": [
"PATH=/opt/unsloth-nb/bin:/opt/unsloth-venv/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin",
"NVARCH=x86_64",
"NVIDIA_REQUIRE_CUDA=cuda\u003e=12.8 brand=unknown,driver\u003e=470,driver\u003c471 brand=grid,driver\u003e=470,driver\u003c471 brand=tesla,driver\u003e=470,driver\u003c471 brand=nvidia,driver\u003e=470,driver\u003c471 brand=quadro,driver\u003e=470,driver\u003c471 brand=quadrortx,driver\u003e=470,driver\u003c471 brand=nvidiartx,driver\u003e=470,driver\u003c471 brand=vapps,driver\u003e=470,driver\u003c471 brand=vpc,driver\u003e=470,driver\u003c471 brand=vcs,driver\u003e=470,driver\u003c471 brand=vws,driver\u003e=470,driver\u003c471 brand=cloudgaming,driver\u003e=470,driver\u003c471 brand=unknown,driver\u003e=535,driver\u003c536 brand=grid,driver\u003e=535,driver\u003c536 brand=tesla,driver\u003e=535,driver\u003c536 brand=nvidia,driver\u003e=535,driver\u003c536 brand=quadro,driver\u003e=535,driver\u003c536 brand=quadrortx,driver\u003e=535,driver\u003c536 brand=nvidiartx,driver\u003e=535,driver\u003c536 brand=vapps,driver\u003e=535,driver\u003c536 brand=vpc,driver\u003e=535,driver\u003c536 brand=vcs,driver\u003e=535,driver\u003c536 brand=vws,driver\u003e=535,driver\u003c536 brand=cloudgaming,driver\u003e=535,driver\u003c536 brand=unknown,driver\u003e=550,driver\u003c551 brand=grid,driver\u003e=550,driver\u003c551 brand=tesla,driver\u003e=550,driver\u003c551 brand=nvidia,driver\u003e=550,driver\u003c551 brand=quadro,driver\u003e=550,driver\u003c551 brand=quadrortx,driver\u003e=550,driver\u003c551 brand=nvidiartx,driver\u003e=550,driver\u003c551 brand=vapps,driver\u003e=550,driver\u003c551 brand=vpc,driver\u003e=550,driver\u003c551 brand=vcs,driver\u003e=550,driver\u003c551 brand=vws,driver\u003e=550,driver\u003c551 brand=cloudgaming,driver\u003e=550,driver\u003c551 brand=unknown,driver\u003e=560,driver\u003c561 brand=grid,driver\u003e=560,driver\u003c561 brand=tesla,driver\u003e=560,driver\u003c561 brand=nvidia,driver\u003e=560,driver\u003c561 brand=quadro,driver\u003e=560,driver\u003c561 brand=quadrortx,driver\u003e=560,driver\u003c561 brand=nvidiartx,driver\u003e=560,driver\u003c561 brand=vapps,driver\u003e=560,driver\u003c561 brand=vpc,driver\u003e=560,driver\u003c561 brand=vcs,driver\u003e=560,driver\u003c561 brand=vws,driver\u003e=560,driver\u003c561 brand=cloudgaming,driver\u003e=560,driver\u003c561 brand=unknown,driver\u003e=565,driver\u003c566 brand=grid,driver\u003e=565,driver\u003c566 brand=tesla,driver\u003e=565,driver\u003c566 brand=nvidia,driver\u003e=565,driver\u003c566 brand=quadro,driver\u003e=565,driver\u003c566 brand=quadrortx,driver\u003e=565,driver\u003c566 brand=nvidiartx,driver\u003e=565,driver\u003c566 brand=vapps,driver\u003e=565,driver\u003c566 brand=vpc,driver\u003e=565,driver\u003c566 brand=vcs,driver\u003e=565,driver\u003c566 brand=vws,driver\u003e=565,driver\u003c566 brand=cloudgaming,driver\u003e=565,driver\u003c566",
"NV_CUDA_CUDART_VERSION=12.8.90-1",
"CUDA_VERSION=12.8.1",
"LD_LIBRARY_PATH=/usr/local/cuda/lib64",
"NVIDIA_VISIBLE_DEVICES=all",
"NVIDIA_DRIVER_CAPABILITIES=compute,utility",
"DEBIAN_FRONTEND=noninteractive",
"PIP_NO_CACHE_DIR=1",
"PYTHONDONTWRITEBYTECODE=1",
"PYTHONUNBUFFERED=1",
"HF_HOME=/workspace/.cache/huggingface",
"TRITON_CACHE_DIR=/workspace/.cache/triton",
"TORCH_CUDA_ARCH_LIST=7.5;8.0;8.6;8.9;9.0;10.0;12.0+PTX",
"UNSLOTH_LLAMA_CPP_PATH=/opt/unsloth/llama.cpp",
"IPYTHONDIR=/opt/unsloth-nb/ipython",
"UNSLOTH_STUDIO_HOME=/opt/unsloth-studio",
"UNSLOTH_STUDIO_APP=/opt/unsloth-studio-app",
"UNSLOTH_STUDIO_DOCUMENTS_HOME=/opt/unsloth-studio/documents",
"UNSLOTH_STUDIO_SKILLS_HOME=/opt/unsloth-studio/skills",
"UV_CACHE_DIR=/opt/unsloth-studio-app/uv-cache",
"UNSLOTH_IMAGE_ALLOW_CPU=1",
"JUPYTER_PORT=8888",
"UNSLOTH_STUDIO_PORT=8000",
"UNSLOTH_ENABLE_SSHD=false",
"UNSLOTH_STUDIO_SHUTDOWN_STOP_TIMEOUT_S=120",
"UNSLOTH_STUDIO_STOP_WAIT_S=150"
],
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],
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"Image": "",
"Volumes": null,
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"Entrypoint": [
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],
"OnBuild": null,
"Labels": {
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"org.opencontainers.image.source": "https://github.com/unslothai/unsloth",
"org.opencontainers.image.title": "unsloth",
"org.opencontainers.image.url": "https://github.com/unslothai/unsloth",
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