Pytorch nlp setup

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

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What its author says it does

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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.

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