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A-Vladimir
Jul 25th, 2025
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  1. (invoke) a-vladimir@Game-X:/mnt/5868f70d-4271-4fe4-a06e-5d1455ac9dc7/Invoke/bitsandbytes$ pip install . --break-system-packages
  2. Defaulting to user installation because normal site-packages is not writeable
  3. Processing /mnt/5868f70d-4271-4fe4-a06e-5d1455ac9dc7/Invoke/bitsandbytes
  4. Installing build dependencies ... done
  5. Getting requirements to build wheel ... done
  6. Preparing metadata (pyproject.toml) ... done
  7. Collecting torch<3,>=2.0 (from bitsandbytes==1.0.0)
  8. Downloading torch-2.7.1-cp312-cp312-manylinux_2_28_x86_64.whl.metadata (29 kB)
  9. Collecting numpy>=1.17 (from bitsandbytes==1.0.0)
  10. Downloading numpy-2.3.2-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.metadata (62 kB)
  11. Requirement already satisfied: filelock in /usr/lib/python3/dist-packages (from torch<3,>=2.0->bitsandbytes==1.0.0) (3.13.1)
  12. Requirement already satisfied: typing-extensions>=4.10.0 in /usr/lib/python3/dist-packages (from torch<3,>=2.0->bitsandbytes==1.0.0) (4.10.0)
  13. Requirement already satisfied: setuptools in /usr/lib/python3/dist-packages (from torch<3,>=2.0->bitsandbytes==1.0.0) (68.1.2)
  14. Collecting sympy>=1.13.3 (from torch<3,>=2.0->bitsandbytes==1.0.0)
  15. Downloading sympy-1.14.0-py3-none-any.whl.metadata (12 kB)
  16. Collecting networkx (from torch<3,>=2.0->bitsandbytes==1.0.0)
  17. Downloading networkx-3.5-py3-none-any.whl.metadata (6.3 kB)
  18. Collecting jinja2 (from torch<3,>=2.0->bitsandbytes==1.0.0)
  19. Downloading jinja2-3.1.6-py3-none-any.whl.metadata (2.9 kB)
  20. Collecting fsspec (from torch<3,>=2.0->bitsandbytes==1.0.0)
  21. Downloading fsspec-2025.7.0-py3-none-any.whl.metadata (12 kB)
  22. Collecting nvidia-cuda-nvrtc-cu12==12.6.77 (from torch<3,>=2.0->bitsandbytes==1.0.0)
  23. Downloading nvidia_cuda_nvrtc_cu12-12.6.77-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)
  24. Collecting nvidia-cuda-runtime-cu12==12.6.77 (from torch<3,>=2.0->bitsandbytes==1.0.0)
  25. Downloading nvidia_cuda_runtime_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (1.5 kB)
  26. Collecting nvidia-cuda-cupti-cu12==12.6.80 (from torch<3,>=2.0->bitsandbytes==1.0.0)
  27. Downloading nvidia_cuda_cupti_cu12-12.6.80-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (1.6 kB)
  28. Collecting nvidia-cudnn-cu12==9.5.1.17 (from torch<3,>=2.0->bitsandbytes==1.0.0)
  29. Downloading nvidia_cudnn_cu12-9.5.1.17-py3-none-manylinux_2_28_x86_64.whl.metadata (1.6 kB)
  30. Collecting nvidia-cublas-cu12==12.6.4.1 (from torch<3,>=2.0->bitsandbytes==1.0.0)
  31. Downloading nvidia_cublas_cu12-12.6.4.1-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (1.5 kB)
  32. Collecting nvidia-cufft-cu12==11.3.0.4 (from torch<3,>=2.0->bitsandbytes==1.0.0)
  33. Downloading nvidia_cufft_cu12-11.3.0.4-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (1.5 kB)
  34. Collecting nvidia-curand-cu12==10.3.7.77 (from torch<3,>=2.0->bitsandbytes==1.0.0)
  35. Downloading nvidia_curand_cu12-10.3.7.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (1.5 kB)
  36. Collecting nvidia-cusolver-cu12==11.7.1.2 (from torch<3,>=2.0->bitsandbytes==1.0.0)
  37. Downloading nvidia_cusolver_cu12-11.7.1.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (1.6 kB)
  38. Collecting nvidia-cusparse-cu12==12.5.4.2 (from torch<3,>=2.0->bitsandbytes==1.0.0)
  39. Downloading nvidia_cusparse_cu12-12.5.4.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (1.6 kB)
  40. Collecting nvidia-cusparselt-cu12==0.6.3 (from torch<3,>=2.0->bitsandbytes==1.0.0)
  41. Downloading nvidia_cusparselt_cu12-0.6.3-py3-none-manylinux2014_x86_64.whl.metadata (6.8 kB)
  42. Collecting nvidia-nccl-cu12==2.26.2 (from torch<3,>=2.0->bitsandbytes==1.0.0)
  43. Downloading nvidia_nccl_cu12-2.26.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (2.0 kB)
  44. Collecting nvidia-nvtx-cu12==12.6.77 (from torch<3,>=2.0->bitsandbytes==1.0.0)
  45. Downloading nvidia_nvtx_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (1.6 kB)
  46. Collecting nvidia-nvjitlink-cu12==12.6.85 (from torch<3,>=2.0->bitsandbytes==1.0.0)
  47. Downloading nvidia_nvjitlink_cu12-12.6.85-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl.metadata (1.5 kB)
  48. Collecting nvidia-cufile-cu12==1.11.1.6 (from torch<3,>=2.0->bitsandbytes==1.0.0)
  49. Downloading nvidia_cufile_cu12-1.11.1.6-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (1.5 kB)
  50. Collecting triton==3.3.1 (from torch<3,>=2.0->bitsandbytes==1.0.0)
  51. Downloading triton-3.3.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.metadata (1.5 kB)
  52. Collecting mpmath<1.4,>=1.1.0 (from sympy>=1.13.3->torch<3,>=2.0->bitsandbytes==1.0.0)
  53. Downloading mpmath-1.3.0-py3-none-any.whl.metadata (8.6 kB)
  54. Requirement already satisfied: MarkupSafe>=2.0 in /usr/lib/python3/dist-packages (from jinja2->torch<3,>=2.0->bitsandbytes==1.0.0) (2.1.5)
  55. Downloading torch-2.7.1-cp312-cp312-manylinux_2_28_x86_64.whl (821.0 MB)
  56. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 821.0/821.0 MB 8.2 MB/s eta 0:00:00
  57. Downloading nvidia_cublas_cu12-12.6.4.1-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (393.1 MB)
  58. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 393.1/393.1 MB 8.2 MB/s eta 0:00:00
  59. Downloading nvidia_cuda_cupti_cu12-12.6.80-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (8.9 MB)
  60. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 8.9/8.9 MB 9.6 MB/s eta 0:00:00
  61. Downloading nvidia_cuda_nvrtc_cu12-12.6.77-py3-none-manylinux2014_x86_64.whl (23.7 MB)
  62. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 23.7/23.7 MB 10.3 MB/s eta 0:00:00
  63. Downloading nvidia_cuda_runtime_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (897 kB)
  64. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 897.7/897.7 kB 10.9 MB/s eta 0:00:00
  65. Downloading nvidia_cudnn_cu12-9.5.1.17-py3-none-manylinux_2_28_x86_64.whl (571.0 MB)
  66. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 571.0/571.0 MB 8.1 MB/s eta 0:00:00
  67. Downloading nvidia_cufft_cu12-11.3.0.4-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (200.2 MB)
  68. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 200.2/200.2 MB 8.1 MB/s eta 0:00:00
  69. Downloading nvidia_cufile_cu12-1.11.1.6-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (1.1 MB)
  70. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.1/1.1 MB 6.9 MB/s eta 0:00:00
  71. Downloading nvidia_curand_cu12-10.3.7.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (56.3 MB)
  72. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 56.3/56.3 MB 8.1 MB/s eta 0:00:00
  73. Downloading nvidia_cusolver_cu12-11.7.1.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (158.2 MB)
  74. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 158.2/158.2 MB 8.1 MB/s eta 0:00:00
  75. Downloading nvidia_cusparse_cu12-12.5.4.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (216.6 MB)
  76. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 216.6/216.6 MB 8.1 MB/s eta 0:00:00
  77. Downloading nvidia_cusparselt_cu12-0.6.3-py3-none-manylinux2014_x86_64.whl (156.8 MB)
  78. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 156.8/156.8 MB 8.1 MB/s eta 0:00:00
  79. Downloading nvidia_nccl_cu12-2.26.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (201.3 MB)
  80. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 201.3/201.3 MB 8.1 MB/s eta 0:00:00
  81. Downloading nvidia_nvjitlink_cu12-12.6.85-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl (19.7 MB)
  82. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 19.7/19.7 MB 8.0 MB/s eta 0:00:00
  83. Downloading nvidia_nvtx_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (89 kB)
  84. Downloading triton-3.3.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (155.7 MB)
  85. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 155.7/155.7 MB 8.1 MB/s eta 0:00:00
  86. Downloading numpy-2.3.2-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (16.6 MB)
  87. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 16.6/16.6 MB 8.1 MB/s eta 0:00:00
  88. Downloading sympy-1.14.0-py3-none-any.whl (6.3 MB)
  89. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 6.3/6.3 MB 8.6 MB/s eta 0:00:00
  90. Downloading mpmath-1.3.0-py3-none-any.whl (536 kB)
  91. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 536.2/536.2 kB 9.3 MB/s eta 0:00:00
  92. Downloading fsspec-2025.7.0-py3-none-any.whl (199 kB)
  93. Downloading jinja2-3.1.6-py3-none-any.whl (134 kB)
  94. Downloading networkx-3.5-py3-none-any.whl (2.0 MB)
  95. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2.0/2.0 MB 7.0 MB/s eta 0:00:00
  96. Building wheels for collected packages: bitsandbytes
  97. Building wheel for bitsandbytes (pyproject.toml) ... done
  98. Created wheel for bitsandbytes: filename=bitsandbytes-1.0.0-cp312-cp312-linux_x86_64.whl size=118383 sha256=393aa7c1c12ebfa0f8a9c195fd21739a08153726b64b18cc8eea26629d14eb31
  99. Stored in directory: /tmp/pip-ephem-wheel-cache-7rk6vccl/wheels/37/23/72/0c854c41bbc056f5734f97470f1caa4991febb46061122ced3
  100. Successfully built bitsandbytes
  101. Installing collected packages: nvidia-cusparselt-cu12, mpmath, triton, sympy, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufile-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, numpy, networkx, jinja2, fsspec, nvidia-cusparse-cu12, nvidia-cufft-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, torch, bitsandbytes
  102. ━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2/23 [triton] WARNING: The scripts proton and proton-viewer are installed in '/home/a-vladimir/.local/bin' which is not on PATH.
  103. Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
  104. ━━━━━╺━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3/23 [sympy] WARNING: The script isympy is installed in '/home/a-vladimir/.local/bin' which is not on PATH.
  105. Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
  106. ━━━━━━━━━━━━━━━━━━━━━━╸━━━━━━━━━━━━━━━━━ 13/23 [numpy] WARNING: The scripts f2py and numpy-config are installed in '/home/a-vladimir/.local/bin' which is not on PATH.
  107. Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
  108. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸━━━ 21/23 [torch] WARNING: The scripts torchfrtrace and torchrun are installed in '/home/a-vladimir/.local/bin' which is not on PATH.
  109. Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
  110. Successfully installed bitsandbytes-1.0.0 fsspec-2025.7.0 jinja2-3.1.6 mpmath-1.3.0 networkx-3.5 numpy-2.3.2 nvidia-cublas-cu12-12.6.4.1 nvidia-cuda-cupti-cu12-12.6.80 nvidia-cuda-nvrtc-cu12-12.6.77 nvidia-cuda-runtime-cu12-12.6.77 nvidia-cudnn-cu12-9.5.1.17 nvidia-cufft-cu12-11.3.0.4 nvidia-cufile-cu12-1.11.1.6 nvidia-curand-cu12-10.3.7.77 nvidia-cusolver-cu12-11.7.1.2 nvidia-cusparse-cu12-12.5.4.2 nvidia-cusparselt-cu12-0.6.3 nvidia-nccl-cu12-2.26.2 nvidia-nvjitlink-cu12-12.6.85 nvidia-nvtx-cu12-12.6.77 sympy-1.14.0 torch-2.7.1 triton-3.3.1
  111. (invoke) a-vladimir@Game-X:/mnt/5868f70d-4271-4fe4-a06e-5d1455ac9dc7/Invoke/bitsandbytes$
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