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coreweave-core-workflow-b

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Run distributed GPU training jobs on CoreWeave with multi-node PyTorch. Use when training models across multiple GPUs, setting up distributed training, or running fine-tuning jobs on CoreWeave H100 clusters. Trigger with phrases like "coreweave training", "coreweave multi-gpu", "distributed training coreweave", "fine-tune on coreweave".

skills/.curated/coreweave-core-workflow-b/SKILL.md

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Nov 12, 2026
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# CoreWeave Training launch and recovery review

> **Community-contributed.** Not affiliated with, endorsed by, or sponsored by CoreWeave, Inc. CoreWeave is a registered trademark of CoreWeave, Inc.

## Overview

Verify distributed training topology, storage and resume evidence before a costly launch.
Use Read to inspect the approved input files, Write the evidence report, and Edit only the proposed local artifact before review.
These procedures complement [CoreWeave’s official skills](https://github.com/coreweave/skills); they do not redistribute or replace that upstream distribution.

## Prerequisites

- The owner-approved organization, cluster context, namespace and resource names.
- A trusted kubeconfig from the approved secret location; no raw credentials in source, logs or terminal history.
- Installed kubectl compatible with the cluster, and authority for each proposed read or change.
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