<jupyter_start><jupyter_text>Install Conda on Google Colab. Last modified 2021.08.04 -->`condacolab` simplifies the setup as much as possible, but there are some gotchas.**⚠️ Read this before continuing!*** The `condacolab` commands need to be run the first Code cell!* Once you run `condacolab.install()`, the Python kernel will be restarted. This is **normal and expected**. After that, you can continue running the cells below like normal.* Do not use the `Run all` option. Run the `condacolab` cell _individually_ and wait for the kernel to restart. **Only then**, you can run all cells if you want.* You can only use the `base` environment. Do not try to create new ones; instead update `base` with either:  * `conda install `  * `conda env update -n base -f environment.yml`* If you want to use GPUs, make sure you are using such an instance before starting!* If you get an error, please raise an issue [here](https://github.com/jaimergp/condacolab/issues).<jupyter_code>!pip install -q condacolab
import condacolab
condacolab.install()
import condacolab
condacolab.check()
!mamba install -q openmm<jupyter_output>Package         Version  Build                Channel                    Size
─────────────────────────────────────────────────────────────────────────────────
  Install:
─────────────────────────────────────────────────────────────────────────────────

[32m  cudatoolkit   [00m   11.0.3  h15472ef_8           conda-forge/linux-64     952 MB
[32m  fftw          [00m    3.3.9  nompi_hcdd671c_101   conda-forge/linux-64       6 MB
[32m  libblas       [00m    3.9.0  8_openblas           conda-forge/linux-64      11 KB
[32m  libcblas      [00m    3.9.0  8_openblas           conda-forge/linux-64      11 KB
[32m  libgfortran-ng[00m    9.3.0  hff62375_18          conda-forge/linux-64      22 KB
[32m  libgfortran5  [00m    9.3.0  hff62375_18          conda-forge/linux-64       2 MB
[32m  liblapack     [00m    3.9.0  8_openblas           conda-forge/linux-64      11 KB
[32m  libopenblas   [00m   0.3.12  pthreads_h4812303_1  conda-forge/linux-64       9 MB
[32m  numpy         [0[...]<jupyter_text>For the CUDA platform to be available, make sure you are using a GPU environment.<jupyter_code>from simtk.testInstallation import main 
main()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.15547856214811606, 'fraction_numerical': 0.059333044608055434, 'mean_word_length': 3.1696750902527078, 'pattern_counts': {'":': 0, '<': 8, '<?xml version=': 0, '>': 9, 'https://': 1, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '228501', 'license': 'Apache-2.0', 'n_tokens_mistral': 894, 'n_tokens_neox': 747, 'n_words': 233, 'path': 'CondaColab_example.ipynb', 'repo_name': 'Mjboothaus/colab_nbdev', 'size': '2309'}