Skill

Pi Pods

1. `pi-mono/packages/pods/README.md` — installation, pod management, model commands, GPU multi-assignment, and pre-defined models.

Install

npx claudepluginhub romiluz13/pi-agent-skills

Tool Access

This skill uses the workspace's default tool permissions.

Preview

1. `pi-mono/packages/pods/README.md` — installation, pod management, model commands, GPU multi-assignment, and pre-defined models.

Supporting Assets

references/CORPUS.md

SKILL.md

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Stats

Stars5

Forks3

Last CommitApr 13, 2026

Actions

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Pi Pods

Grounding

pi-mono/packages/pods/README.md — installation, pod management, model commands, GPU multi-assignment, and pre-defined models.

pi-mono/packages/pods/src/ — CLI commands implementation if needing deeper args validation.

Invariants

Auto-assignment: When running multiple models on the same pod, pi automatically assigns them to different GPUs.

Parameter Ignorance: When passing custom vLLM args with --vllm, the default CLI shortcuts for --memory, --context, and --gpus are ignored.

Workflows

Setup Pod: Use pi pods setup <name> "<ssh>" along with --mount for shared NFS storage (DataCrunch) or network volumes (RunPod).

Start Pre-defined Model: Use pi start <model> --name <name> for known agentic models (Qwen, GLM, GPT-OSS). The tool calling parsers are automatically configured.

Custom vLLM Args: Pass specific settings (e.g. tensor parallelism) using --vllm --tensor-parallel-size <N>.

Anti-patterns

Do not manually construct tool-calling parsers for pre-defined models like Qwen or GLM; pi configures hermes or glm4_moe automatically.

Do not assume models are downloaded redundantly on DataCrunch; emphasize the NFS shared models path (/mnt/hf-models).

Pi Pods

Grounding

pi-mono/packages/pods/README.md — installation, pod management, model commands, GPU multi-assignment, and pre-defined models.
pi-mono/packages/pods/src/ — CLI commands implementation if needing deeper args validation.

Invariants

Auto-assignment: When running multiple models on the same pod, pi automatically assigns them to different GPUs.
Parameter Ignorance: When passing custom vLLM args with --vllm, the default CLI shortcuts for --memory, --context, and --gpus are ignored.

Workflows

Setup Pod: Use pi pods setup <name> "<ssh>" along with --mount for shared NFS storage (DataCrunch) or network volumes (RunPod).
Start Pre-defined Model: Use pi start <model> --name <name> for known agentic models (Qwen, GLM, GPT-OSS). The tool calling parsers are automatically configured.
Custom vLLM Args: Pass specific settings (e.g. tensor parallelism) using --vllm --tensor-parallel-size <N>.

Anti-patterns

Do not manually construct tool-calling parsers for pre-defined models like Qwen or GLM; pi configures hermes or glm4_moe automatically.
Do not assume models are downloaded redundantly on DataCrunch; emphasize the NFS shared models path (/mnt/hf-models).