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Pytorch nlp setup

Skill cxcscmu/SkillLearnBench/skills/b4-skill-creator-claude-opus-4-6/nlp-paper-reproduction/pytorch-nlp-setup

Set up Python environments for NLP/ML projects using PyTorch, transformers, and TRL. Use this skill when installing dependencies for preference optimization, RLHF, or transformer-based training pipelines.From its SKILL.md

Install
npx -y skills add cxcscmu/SkillLearnBench --skill pytorch-nlp-setup

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SKILL.md

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PyTorch NLP Environment Setup

Standard Stack for Preference Optimization Projects

pip install torch transformers datasets accelerate trl peft wandb numpy

Version Compatibility Notes

  • TRL (Transformer Reinforcement Learning) provides base trainers like CPOTrainer, DPOTrainer
  • Older TRL versions (< 0.8) have different import paths for utilities
  • Check from trl.trainer.utils import DPODataCollatorWithPadding availability
  • For trl_sanitze_kwargs_for_tagging (note: typo is intentional in some versions)

Common Issues

  • If from trl.import_utils import is_peft_available fails, check TRL version
  • Some projects pin specific transformers/TRL versions — check requirements.txt or setup.py
  • CUDA availability: use torch.device("cuda:0" if torch.cuda.is_available() else "cpu")

Running Unit Tests

cd /path/to/project && python -m pytest unit_test/ -v
# or
cd /path/to/project && python -m unittest unit_test.unit_test_1

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