coreweave-pack

Integrate CoreWeave deployments into CI/CD pipelines with GitHub Actions. Use when automating container builds, deploying inference services from CI, or validating GPU manifests in pull requests. Trigger with phrases like "coreweave CI", "coreweave github actions", "coreweave pipeline", "automate coreweave deploy".

Diagnose and fix CoreWeave GPU scheduling, pod, and networking errors. Use when pods are stuck Pending, GPUs are not allocated, or experiencing CUDA and NCCL errors. Trigger with phrases like "coreweave error", "coreweave pod pending", "coreweave gpu not found", "coreweave debug", "fix coreweave".

Deploy KServe InferenceService on CoreWeave with autoscaling and GPU scheduling. Use when serving ML models with KServe, configuring scale-to-zero, or deploying production inference endpoints on CoreWeave. Trigger with phrases like "coreweave inference service", "coreweave kserve", "coreweave model serving", "deploy model on coreweave".

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".

Optimize CoreWeave GPU cloud costs with right-sizing and scheduling. Use when reducing GPU spend, selecting cost-effective instances, or implementing scale-to-zero for dev workloads. Trigger with phrases like "coreweave cost", "coreweave pricing", "reduce coreweave spend", "coreweave budget".