Instructions to use smostafanejad/gen-mlm-cismi-bert-wordpiece with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smostafanejad/gen-mlm-cismi-bert-wordpiece with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("smostafanejad/gen-mlm-cismi-bert-wordpiece", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| name: bad_env | |
| channels: | |
| - conda-forge | |
| - defaults | |
| dependencies: | |
| - _libgcc_mutex=0.1=main | |
| - _openmp_mutex=5.1=1_gnu | |
| - asttokens=3.0.0=pyhd8ed1ab_1 | |
| - bzip2=1.0.8=h5eee18b_6 | |
| - ca-certificates=2025.4.26=hbd8a1cb_0 | |
| - comm=0.2.2=pyhd8ed1ab_1 | |
| - debugpy=1.8.11=py310h6a678d5_0 | |
| - decorator=5.2.1=pyhd8ed1ab_0 | |
| - entrypoints=0.4=pyhd8ed1ab_1 | |
| - exceptiongroup=1.2.2=pyhd8ed1ab_1 | |
| - executing=2.2.0=pyhd8ed1ab_0 | |
| - ipykernel=6.29.5=pyh3099207_0 | |
| - ipython=8.36.0=pyh907856f_0 | |
| - jedi=0.19.2=pyhd8ed1ab_1 | |
| - jupyter_client=7.3.4=pyhd8ed1ab_0 | |
| - jupyter_core=5.7.2=pyh31011fe_1 | |
| - ld_impl_linux-64=2.40=h12ee557_0 | |
| - libffi=3.4.4=h6a678d5_1 | |
| - libgcc-ng=11.2.0=h1234567_1 | |
| - libgomp=11.2.0=h1234567_1 | |
| - libsodium=1.0.18=h36c2ea0_1 | |
| - libstdcxx-ng=11.2.0=h1234567_1 | |
| - libuuid=1.41.5=h5eee18b_0 | |
| - matplotlib-inline=0.1.7=pyhd8ed1ab_1 | |
| - ncurses=6.4=h6a678d5_0 | |
| - nest-asyncio=1.6.0=pyhd8ed1ab_1 | |
| - openssl=3.0.16=h5eee18b_0 | |
| - packaging=25.0=pyh29332c3_1 | |
| - parso=0.8.4=pyhd8ed1ab_1 | |
| - pexpect=4.9.0=pyhd8ed1ab_1 | |
| - pickleshare=0.7.5=pyhd8ed1ab_1004 | |
| - pip=25.1=pyhc872135_2 | |
| - platformdirs=4.3.7=pyh29332c3_0 | |
| - prompt-toolkit=3.0.51=pyha770c72_0 | |
| - ptyprocess=0.7.0=pyhd8ed1ab_1 | |
| - pure_eval=0.2.3=pyhd8ed1ab_1 | |
| - pygments=2.19.1=pyhd8ed1ab_0 | |
| - python=3.10.16=he870216_1 | |
| - python-dateutil=2.9.0.post0=pyhff2d567_1 | |
| - python_abi=3.10=2_cp310 | |
| - pyzmq=26.2.0=py310h6a678d5_0 | |
| - readline=8.2=h5eee18b_0 | |
| - setuptools=78.1.1=py310h06a4308_0 | |
| - six=1.17.0=pyhd8ed1ab_0 | |
| - sqlite=3.45.3=h5eee18b_0 | |
| - stack_data=0.6.3=pyhd8ed1ab_1 | |
| - tk=8.6.14=h39e8969_0 | |
| - tornado=6.1=py310h5764c6d_3 | |
| - traitlets=5.14.3=pyhd8ed1ab_1 | |
| - typing_extensions=4.13.2=pyh29332c3_0 | |
| - wcwidth=0.2.13=pyhd8ed1ab_1 | |
| - wheel=0.45.1=py310h06a4308_0 | |
| - xz=5.6.4=h5eee18b_1 | |
| - zeromq=4.3.5=h6a678d5_0 | |
| - zlib=1.2.13=h5eee18b_1 | |
| - pip: | |
| - accelerate==1.6.0 | |
| - aiohappyeyeballs==2.6.1 | |
| - aiohttp==3.11.18 | |
| - aiosignal==1.3.2 | |
| - async-timeout==5.0.1 | |
| - attrs==25.3.0 | |
| - certifi==2025.4.26 | |
| - charset-normalizer==3.4.2 | |
| - datasets==3.5.1 | |
| - dill==0.3.8 | |
| - filelock==3.18.0 | |
| - frozenlist==1.6.0 | |
| - fsspec==2025.3.0 | |
| - huggingface-hub==0.30.2 | |
| - idna==3.10 | |
| - jinja2==3.1.6 | |
| - markupsafe==3.0.2 | |
| - mpmath==1.3.0 | |
| - multidict==6.4.3 | |
| - multiprocess==0.70.16 | |
| - networkx==3.4.2 | |
| - numpy==2.2.5 | |
| - 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 | |
| - pandas==2.2.3 | |
| - propcache==0.3.1 | |
| - psutil==7.0.0 | |
| - pyarrow==20.0.0 | |
| - pytz==2025.2 | |
| - pyyaml==6.0.2 | |
| - regex==2024.11.6 | |
| - requests==2.32.3 | |
| - safetensors==0.5.3 | |
| - sympy==1.14.0 | |
| - tokenizers==0.21.1 | |
| - torch==2.7.0 | |
| - tqdm==4.67.1 | |
| - transformers==4.51.3 | |
| - triton==3.3.0 | |
| - tzdata==2025.2 | |
| - urllib3==2.4.0 | |
| - xxhash==3.5.0 | |
| - yarl==1.20.0 | |