Software Development
Huawei Cloud Cloudrobo Weight Layout
Standard directory layout and naming conventions for saving model weights (checkpoints). Use this skill when the user needs to implement checkpoint saving in a training script, restructure an existing checkpoint/output directory layout, decide where to store checkpoint weights and final weights, name weight files, or write a loader/deployment path resolver that consumes checkpoints. Applies to any deep learning training pipeline (VLA / robot foundation models, LLM fine-tuning, diffusion models, etc.) — not tied to a single codebase. Also triggers when the user simply says "save weights", "checkpoint directory", "output layout", or asks where model weights should go after training.
- Publisher / source
- huaweicloud/huaweicloud-skills (found on skills.sh)
- Upstream record
- huaweicloud/huaweicloud-skills
- Version
- Version 1
- Published
- Publication review
- Approved for publication
- Content fingerprint
01f563bacbb6245fa018e302d4c2c163a082ed0b69032dc5178d78a2d1cc51fd