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Environment setup

Skill cxcscmu/SkillLearnBench/skills/b4-skill-creator-gemini-3.1-flash-lite-preview/nlp-paper-reproduction/environment-setup

[COLM'26] SkillLearnBench is the first benchmark for evaluating continual learning methods that automatically generate agent skills.

Install
npx -y skills add cxcscmu/SkillLearnBench --skill environment-setup

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Procedures for setting up the environment for research projects involving Python, PyTorch, and NLP models. Use whenever environment requirements (environment.yml) are present.

SKILL.md

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Environment Setup for NLP Research

When dealing with deep learning research repositories, follow these steps:

  1. Review Requirements: Inspect environment.yml or requirements.txt to identify dependencies.
  2. Version Checks:
    • python -VV to check the python version.
    • pip freeze to check installed packages.
  3. Environment Creation:
    • Use conda env update --file environment.yml or standard pip requirements installation if conda is not available.
  4. Validation:
    • Verify that all necessary libraries for training/evaluation are available.
    • Ensure hardware acceleration (CUDA/ROCm) is correctly configured if needed.
    • Log the final environment state.
  5. Consistency:
    • Record the environment state to a file (e.g., python_info.txt) to allow for replication.

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