일단 수많은 에러와 cuda version과 wheel, nvcc 버전의 충돌 오류를 마주한 저는...
결국 miniforge를 아예 밀고 다시 재설치를 하였답니다
오류를 해결하다 보니 점점 라이브러리 경로랑 버전도 다 꼬여서 그냥 밀고 재설치하는 게 제일 정답이라는 팩트를 알려드리며..
아래와 같이 명령어를 순서대로 그대로 수행하면 일단 무조건 오류없이 되는 것 같네요 (다른 컴퓨터들에서도 테스트 완료)
명령어와 함께 해당 명령어 입력 후 출력된 제 터미널 결과들도 함께 첨부하였으니 확인하면 좋을 듯 합니다.
에러는 당연히 없었고 그 흔한 warning 문구도 나오지 않았어요~ (와!)
단 아래 환경은 ubuntu 24.04, cuda version==13.0 조건이니 이 조건이 아니라면 명령어 수정이 필요할 수도 있습니다.
cuda version은 nvidia-smi 명령어를 입력하면 확인할 수 있습니다.
0. miniforge 설치 방법 (리드미 참고)
https://github.com/conda-forge/miniforge#install
GitHub - conda-forge/miniforge: A conda-forge distribution.
A conda-forge distribution. Contribute to conda-forge/miniforge development by creating an account on GitHub.
github.com
1. miniforge 재설치 후 python과 conda의 경로 확인
(base) sallysooo@labor:~$ which python
/home/sallysooo/miniforge3/bin/python
(base) sallysooo@labor:~$ which conda
/home/sallysooo/miniforge3/bin/conda
2. 가상환경 생성 (이름은 자율, 필자는 lens라는 이름으로 생성)
# 가상환경 생성
(base) sallysooo@labor:~$ mamba create -n lens
Empty environment created at prefix: /home/sallysooo/miniforge3/envs/lens
# 가상환경 활성화
(base) sallysooo@labor:~$ mamba activate lens
3. python은 3.14, nvcc는 13.0 버전으로 설치
$ mamba install -y python=3.14 pip cuda-nvcc=13.0(lens) sallysooo@labor:~$ mamba install -y python=3.14 pip cuda-nvcc=13.0
conda-forge/noarch 24.8MB @ 4.2MB/s 5.9s
conda-forge/linux-64 51.2MB @ 6.0MB/s 8.5s
Transaction
Prefix: /home/sallysooo/miniforge3/envs/lens
Updating specs:
- python=3.14
- pip
- cuda-nvcc=13.0
Package Version Build Channel Size
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Install:
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+ _openmp_mutex 4.5 20_gnu conda-forge 29kB
+ binutils_impl_linux-64 2.45.1 default_hfdba357_101 conda-forge 4MB
+ binutils_linux-64 2.45.1 default_h4852527_101 conda-forge 36kB
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+ cuda-nvcc 13.0.88 hcdd1206_6 conda-forge 25kB
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+ cuda-nvvm-impl 13.0.88 h4bc722e_0 conda-forge 22MB
+ cuda-nvvm-tools 13.0.88 h4bc722e_0 conda-forge 25MB
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+ gxx_linux-64 15.2.0 h1fb793f_21 conda-forge 27kB
+ icu 78.2 h33c6efd_0 conda-forge Cached
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+ ld_impl_linux-64 2.45.1 default_hbd61a6d_101 conda-forge Cached
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+ libffi 3.5.2 h3435931_0 conda-forge Cached
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+ libgcc-devel_linux-64 15.2.0 hcc6f6b0_118 conda-forge 3MB
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+ liblzma 5.8.2 hb03c661_0 conda-forge Cached
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+ libnvptxcompiler-dev 13.0.88 ha770c72_0 conda-forge 28kB
+ libnvptxcompiler-dev_linux-64 13.0.88 ha770c72_0 conda-forge 15MB
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+ libuuid 2.41.3 h5347b49_0 conda-forge Cached
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+ pip 26.0.1 pyh145f28c_0 conda-forge Cached
+ python 3.14.3 h32b2ec7_101_cp314 conda-forge 37MB
+ python_abi 3.14 8_cp314 conda-forge 7kB
+ readline 8.3 h853b02a_0 conda-forge Cached
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+ tk 8.6.13 noxft_h366c992_103 conda-forge Cached
+ tzdata 2025c hc9c84f9_1 conda-forge Cached
+ zstd 1.5.7 hb78ec9c_6 conda-forge Cached
Summary:
Install: 56 packages
Total download: 314MB
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Transaction starting
cuda-nvvm-tools 24.5MB @ 1.9MB/s 12.7s
cuda-nvcc-tools 28.8MB @ 1.8MB/s 16.4s
python 36.7MB @ 1.9MB/s 18.9s
sysroot_linux-64 41.5MB @ 1.9MB/s 21.2s
cuda-nvvm-impl 21.7MB @ 1.7MB/s 12.6s
gxx_impl_linux-64 15.6MB @ 2.0MB/s 7.7s
libnvptxcompiler-dev_linux-64 15.0MB @ 2.3MB/s 6.6s
libstdcxx-devel_linux-64 20.7MB @ 1.6MB/s 13.0s
binutils_impl_linux-64 3.7MB @ 2.3MB/s 1.6s
libsanitizer 8.1MB @ 1.9MB/s 4.2s
libstdcxx 5.9MB @ 1.7MB/s 3.4s
cuda-cccl_linux-64 1.1MB @ 1.8MB/s 0.6s
kernel-headers_linux-64 1.5MB @ 2.1MB/s 0.7s
libgomp 603.3kB @ 1.9MB/s 0.3s
libgcc 1.0MB @ 2.4MB/s 0.4s
bzip2 260.2kB @ 1.4MB/s 0.2s
cuda-cudart-dev_linux-64 385.6kB @ 1.7MB/s 0.2s
libgcc-devel_linux-64 3.1MB @ 2.2MB/s 1.4s
cuda-crt-dev_linux-64 95.7kB @ 163.8kB/s 0.1s
cuda-cudart_linux-64 185.3kB @ 1.1MB/s 0.1s
libexpat 76.8kB @ 1.1MB/s 0.1s
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binutils_linux-64 36.1kB @ 389.2kB/s 0.1s
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cuda-nvcc-dev_linux-64 28.9kB @ ??.?MB/s 0.0s
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cuda-cudart 24.0kB @ ??.?MB/s 0.0s
python_abi 7.0kB @ ??.?MB/s 0.0s
cuda-version 21.5kB @ ??.?MB/s 0.1s
gcc_impl_linux-64 81.8MB @ 2.5MB/s 33.2s
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4. 기타 라이브러리들 설치
- 주의) cuda 13.0 버전이라면 마지막의 url을 그대로 입력하면 되지만, 버전이 다르다면 url 끝의 숫자를 변경해야 함
$ pip install pandas pyarrow numpy scipy matplotlib ipython scikit-learn pillow jupyter openpyxl tqdm seaborn tabulate scienceplots wandb transformers polars tokenizers cantools pyarrow torchinfo torch torchvision torchaudio accelerate scapy --extra-index-url https://download.pytorch.org/whl/cu130(lens) sallysooo@labor:~$ pip install pandas pyarrow numpy scipy matplotlib ipython scikit-learn pillow jupyter openpyxl tqdm seaborn tabulate scienceplots wandb transformers polars tokenizers cantools pyarrow torchinfo torch torchvision torchaudio accelerate scapy --extra-index-url https://download.pytorch.org/whl/cu130
Looking in indexes: https://pypi.org/simple, https://download.pytorch.org/whl/cu130
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Using cached annotated_doc-0.0.4-py3-none-any.whl (5.3 kB)
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Using cached markdown_it_py-4.0.0-py3-none-any.whl (87 kB)
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Using cached uri_template-1.3.0-py3-none-any.whl (11 kB)
Using cached wcwidth-0.6.0-py3-none-any.whl (94 kB)
Installing collected packages: webencodings, textparser, pure-eval, ptyprocess, nvidia-cusparselt-cu13, mpmath, fastjsonschema, crccheck, wrapt, widgetsnbextension, websocket-client, webcolors, wcwidth, urllib3, uri-template, tzdata, typing-extensions, triton, traitlets, tqdm, tornado, torchinfo, tinycss2, threadpoolctl, tabulate, sympy, soupsieve, smmap, six, shellingham, setuptools, send2trash, scapy, safetensors, rpds-py, rfc3986-validator, regex, pyzmq, pyyaml, python-json-logger, pyparsing, pygments, pycparser, pyarrow, psutil, protobuf, prometheus-client, polars-runtime-32, platformdirs, pillow, pexpect, parso, pandocfilters, packaging, nvidia-nvtx, nvidia-nvshmem-cu13, nvidia-nvjitlink, nvidia-nccl-cu13, nvidia-curand, nvidia-cufile, nvidia-cuda-runtime, nvidia-cuda-nvrtc, nvidia-cuda-cupti, nvidia-cublas, numpy, networkx, nest-asyncio, mistune, mdurl, MarkupSafe, lark, kiwisolver, jupyterlab_widgets, jupyterlab-pygments, jsonpointer, json5, joblib, idna, hf-xet, h11, fsspec, fqdn, fonttools, filelock, executing, et-xmlfile, diskcache, defusedxml, decorator, debugpy, cycler, cuda-pathfinder, comm, click, charset_normalizer, certifi, bleach, bitstruct, babel, attrs, async-lru, asttokens, argparse_addons, annotated-types, annotated-doc, typing-inspection, terminado, stack_data, sentry-sdk, scipy, rfc3987-syntax, rfc3339-validator, requests, referencing, python-dateutil, python-can, pydantic-core, prompt_toolkit, polars, openpyxl, nvidia-cusparse, nvidia-cufft, nvidia-cudnn-cu13, matplotlib-inline, markdown-it-py, jupyter-core, jinja2, jedi, ipython-pygments-lexers, httpcore, gitdb, cuda-bindings, contourpy, cffi, beautifulsoup4, anyio, scikit-learn, rich, pydantic, pandas, nvidia-cusolver, matplotlib, jupyter-server-terminals, jupyter-client, jsonschema-specifications, ipython, httpx, gitpython, cantools, arrow, argon2-cffi-bindings, wandb, typer, torch, seaborn, scienceplots, jsonschema, isoduration, ipywidgets, ipykernel, argon2-cffi, typer-slim, torchvision, torchaudio, nbformat, jupyter-console, nbclient, jupyter-events, huggingface-hub, tokenizers, nbconvert, accelerate, transformers, jupyter-server, notebook-shim, jupyterlab-server, jupyter-lsp, jupyterlab, notebook, jupyter
Successfully installed MarkupSafe-3.0.3 accelerate-1.12.0 annotated-doc-0.0.4 annotated-types-0.7.0 anyio-4.12.1 argon2-cffi-25.1.0 argon2-cffi-bindings-25.1.0 argparse_addons-0.12.0 arrow-1.4.0 asttokens-3.0.1 async-lru-2.2.0 attrs-25.4.0 babel-2.18.0 beautifulsoup4-4.14.3 bitstruct-8.22.1 bleach-6.3.0 cantools-41.1.1 certifi-2026.1.4 cffi-2.0.0 charset_normalizer-3.4.4 click-8.3.1 comm-0.2.3 contourpy-1.3.3 crccheck-1.3.1 cuda-bindings-13.0.3 cuda-pathfinder-1.3.4 cycler-0.12.1 debugpy-1.8.20 decorator-5.2.1 defusedxml-0.7.1 diskcache-5.6.3 et-xmlfile-2.0.0 executing-2.2.1 fastjsonschema-2.21.2 filelock-3.24.3 fonttools-4.61.1 fqdn-1.5.1 fsspec-2026.2.0 gitdb-4.0.12 gitpython-3.1.46 h11-0.16.0 hf-xet-1.2.0 httpcore-1.0.9 httpx-0.28.1 huggingface-hub-1.4.1 idna-3.11 ipykernel-7.2.0 ipython-9.10.0 ipython-pygments-lexers-1.1.1 ipywidgets-8.1.8 isoduration-20.11.0 jedi-0.19.2 jinja2-3.1.6 joblib-1.5.3 json5-0.13.0 jsonpointer-3.0.0 jsonschema-4.26.0 jsonschema-specifications-2025.9.1 jupyter-1.1.1 jupyter-client-8.8.0 jupyter-console-6.6.3 jupyter-core-5.9.1 jupyter-events-0.12.0 jupyter-lsp-2.3.0 jupyter-server-2.17.0 jupyter-server-terminals-0.5.4 jupyterlab-4.5.4 jupyterlab-pygments-0.3.0 jupyterlab-server-2.28.0 jupyterlab_widgets-3.0.16 kiwisolver-1.4.9 lark-1.3.1 markdown-it-py-4.0.0 matplotlib-3.10.8 matplotlib-inline-0.2.1 mdurl-0.1.2 mistune-3.2.0 mpmath-1.3.0 nbclient-0.10.4 nbconvert-7.17.0 nbformat-5.10.4 nest-asyncio-1.6.0 networkx-3.6.1 notebook-7.5.3 notebook-shim-0.2.4 numpy-2.4.2 nvidia-cublas-13.1.0.3 nvidia-cuda-cupti-13.0.85 nvidia-cuda-nvrtc-13.0.88 nvidia-cuda-runtime-13.0.96 nvidia-cudnn-cu13-9.15.1.9 nvidia-cufft-12.0.0.61 nvidia-cufile-1.15.1.6 nvidia-curand-10.4.0.35 nvidia-cusolver-12.0.4.66 nvidia-cusparse-12.6.3.3 nvidia-cusparselt-cu13-0.8.0 nvidia-nccl-cu13-2.28.9 nvidia-nvjitlink-13.0.88 nvidia-nvshmem-cu13-3.4.5 nvidia-nvtx-13.0.85 openpyxl-3.1.5 packaging-26.0 pandas-3.0.1 pandocfilters-1.5.1 parso-0.8.6 pexpect-4.9.0 pillow-12.1.1 platformdirs-4.9.2 polars-1.38.1 polars-runtime-32-1.38.1 prometheus-client-0.24.1 prompt_toolkit-3.0.52 protobuf-6.33.5 psutil-7.2.2 ptyprocess-0.7.0 pure-eval-0.2.3 pyarrow-23.0.1 pycparser-3.0 pydantic-2.12.5 pydantic-core-2.41.5 pygments-2.19.2 pyparsing-3.3.2 python-can-4.6.1 python-dateutil-2.9.0.post0 python-json-logger-4.0.0 pyyaml-6.0.3 pyzmq-27.1.0 referencing-0.37.0 regex-2026.2.19 requests-2.32.5 rfc3339-validator-0.1.4 rfc3986-validator-0.1.1 rfc3987-syntax-1.1.0 rich-14.3.3 rpds-py-0.30.0 safetensors-0.7.0 scapy-2.7.0 scienceplots-2.2.0 scikit-learn-1.8.0 scipy-1.17.1 seaborn-0.13.2 send2trash-2.1.0 sentry-sdk-2.53.0 setuptools-82.0.0 shellingham-1.5.4 six-1.17.0 smmap-5.0.2 soupsieve-2.8.3 stack_data-0.6.3 sympy-1.14.0 tabulate-0.9.0 terminado-0.18.1 textparser-0.24.0 threadpoolctl-3.6.0 tinycss2-1.4.0 tokenizers-0.22.2 torch-2.10.0+cu130 torchaudio-2.10.0+cu130 torchinfo-1.8.0 torchvision-0.25.0+cu130 tornado-6.5.4 tqdm-4.67.3 traitlets-5.14.3 transformers-5.2.0 triton-3.6.0 typer-0.24.1 typer-slim-0.24.0 typing-extensions-4.15.0 typing-inspection-0.4.2 tzdata-2025.3 uri-template-1.3.0 urllib3-2.6.3 wandb-0.25.0 wcwidth-0.6.0 webcolors-25.10.0 webencodings-0.5.1 websocket-client-1.9.0 widgetsnbextension-4.0.15 wrapt-1.17.3
5. 잘 설치되었는지 보기 위해 python에서 torch 버전 확인
(lens) sallysooo@labor:~$ python
Python 3.14.3 | packaged by conda-forge | (main, Feb 9 2026, 21:56:02) [GCC 14.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
torch>>> torch.__version__
'2.10.0+cu130'
6. 여기까지 문제없이 잘 설치되었다면 마지막으로 mamba-ssm과 casual-conv1d 설치
- 이때 5번 단계와 동일하게 끝에 url 옵션을 다시 한 번 넣어줘야 커널 버전이 지정되게 됩니다.
$ pip install mamba-ssm causal-conv1d --extra-index-url https://download.pytorch.org/whl/cu130(lens) sallysooo@labor:~$ pip install mamba-ssm causal-conv1d --extra-index-url https://download.pytorch.org/whl/cu130
Looking in indexes: https://pypi.org/simple, https://download.pytorch.org/whl/cu130
Collecting mamba-ssm
Using cached mamba_ssm-2.3.0.tar.gz (121 kB)
Installing build dependencies ... done
Getting requirements to build wheel ... done
Preparing metadata (pyproject.toml) ... done
Collecting causal-conv1d
Using cached causal_conv1d-1.6.0.tar.gz (29 kB)
Installing build dependencies ... done
Getting requirements to build wheel ... done
Preparing metadata (pyproject.toml) ... done
Requirement already satisfied: torch in ./miniforge3/envs/lens/lib/python3.14/site-packages (from mamba-ssm) (2.10.0+cu130)
Requirement already satisfied: triton in ./miniforge3/envs/lens/lib/python3.14/site-packages (from mamba-ssm) (3.6.0)
Collecting ninja (from mamba-ssm)
Using cached ninja-1.13.0-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.metadata (5.1 kB)
Collecting einops (from mamba-ssm)
Using cached einops-0.8.2-py3-none-any.whl.metadata (13 kB)
Requirement already satisfied: transformers in ./miniforge3/envs/lens/lib/python3.14/site-packages (from mamba-ssm) (5.2.0)
Requirement already satisfied: packaging in ./miniforge3/envs/lens/lib/python3.14/site-packages (from mamba-ssm) (26.0)
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Requirement already satisfied: filelock in ./miniforge3/envs/lens/lib/python3.14/site-packages (from torch->mamba-ssm) (3.24.3)
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Requirement already satisfied: nvidia-cuda-cupti==13.0.85 in ./miniforge3/envs/lens/lib/python3.14/site-packages (from torch->mamba-ssm) (13.0.85)
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Requirement already satisfied: nvidia-cublas==13.1.0.3 in ./miniforge3/envs/lens/lib/python3.14/site-packages (from torch->mamba-ssm) (13.1.0.3)
Requirement already satisfied: nvidia-cufft==12.0.0.61 in ./miniforge3/envs/lens/lib/python3.14/site-packages (from torch->mamba-ssm) (12.0.0.61)
Requirement already satisfied: nvidia-curand==10.4.0.35 in ./miniforge3/envs/lens/lib/python3.14/site-packages (from torch->mamba-ssm) (10.4.0.35)
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Requirement already satisfied: nvidia-cusparselt-cu13==0.8.0 in ./miniforge3/envs/lens/lib/python3.14/site-packages (from torch->mamba-ssm) (0.8.0)
Requirement already satisfied: nvidia-nccl-cu13==2.28.9 in ./miniforge3/envs/lens/lib/python3.14/site-packages (from torch->mamba-ssm) (2.28.9)
Requirement already satisfied: nvidia-nvshmem-cu13==3.4.5 in ./miniforge3/envs/lens/lib/python3.14/site-packages (from torch->mamba-ssm) (3.4.5)
Requirement already satisfied: nvidia-nvtx==13.0.85 in ./miniforge3/envs/lens/lib/python3.14/site-packages (from torch->mamba-ssm) (13.0.85)
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Requirement already satisfied: nvidia-cufile==1.15.1.6 in ./miniforge3/envs/lens/lib/python3.14/site-packages (from torch->mamba-ssm) (1.15.1.6)
Requirement already satisfied: cuda-pathfinder~=1.1 in ./miniforge3/envs/lens/lib/python3.14/site-packages (from cuda-bindings==13.0.3->torch->mamba-ssm) (1.3.4)
Requirement already satisfied: mpmath<1.4,>=1.1.0 in ./miniforge3/envs/lens/lib/python3.14/site-packages (from sympy>=1.13.3->torch->mamba-ssm) (1.3.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./miniforge3/envs/lens/lib/python3.14/site-packages (from jinja2->torch->mamba-ssm) (3.0.3)
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Requirement already satisfied: regex!=2019.12.17 in ./miniforge3/envs/lens/lib/python3.14/site-packages (from transformers->mamba-ssm) (2026.2.19)
Requirement already satisfied: tokenizers<=0.23.0,>=0.22.0 in ./miniforge3/envs/lens/lib/python3.14/site-packages (from transformers->mamba-ssm) (0.22.2)
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Requirement already satisfied: rich>=12.3.0 in ./miniforge3/envs/lens/lib/python3.14/site-packages (from typer>=0.24.0->typer-slim->transformers->mamba-ssm) (14.3.3)
Requirement already satisfied: annotated-doc>=0.0.2 in ./miniforge3/envs/lens/lib/python3.14/site-packages (from typer>=0.24.0->typer-slim->transformers->mamba-ssm) (0.0.4)
Requirement already satisfied: markdown-it-py>=2.2.0 in ./miniforge3/envs/lens/lib/python3.14/site-packages (from rich>=12.3.0->typer>=0.24.0->typer-slim->transformers->mamba-ssm) (4.0.0)
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Requirement already satisfied: mdurl~=0.1 in ./miniforge3/envs/lens/lib/python3.14/site-packages (from markdown-it-py>=2.2.0->rich>=12.3.0->typer>=0.24.0->typer-slim->transformers->mamba-ssm) (0.1.2)
Using cached einops-0.8.2-py3-none-any.whl (65 kB)
Using cached ninja-1.13.0-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (180 kB)
Building wheels for collected packages: mamba-ssm, causal-conv1d
Building wheel for mamba-ssm (pyproject.toml) ... done
Created wheel for mamba-ssm: filename=mamba_ssm-2.3.0-cp314-cp314-linux_x86_64.whl size=349676774 sha256=b8dea4d927ba508c4179fa4c8fa04b3c0a6f815294d5a8e510c47ed704c27157
Stored in directory: /home/sallysooo/.cache/pip/wheels/21/5e/8b/bb6a9f723b3b8e67be5c1ea0a0d6c3b3c42b4c9c6a650f3162
Building wheel for causal-conv1d (pyproject.toml) ... done
Created wheel for causal-conv1d: filename=causal_conv1d-1.6.0-cp314-cp314-linux_x86_64.whl size=202636160 sha256=f08f23b2177b5978ebd1adb7b7d8d029a74d4798dbee632e4bff96f74905c4fe
Stored in directory: /home/sallysooo/.cache/pip/wheels/a5/b4/35/bbccb7a82c24fae98b238cdfb17a87c7756477eba9b3da3c31
Successfully built mamba-ssm causal-conv1d
Installing collected packages: ninja, einops, causal-conv1d, mamba-ssm
Successfully installed causal-conv1d-1.6.0 einops-0.8.2 mamba-ssm-2.3.0 ninja-1.13.0
(lens) sallysooo@labor:~$
설치 끝!
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