Pilot Model Share

Distribute ML model files with model card metadata and version tracking over Pilot Protocol. Use this skill when: 1. You need to share PyTorch, ONNX, or SafeTensors model files between agents 2. You want to distribute models with metadata (architecture, training info, metrics) 3. You need model versioning and compatibility checking Do NOT use this skill when: - You need to transfer datasets (use pilot-dataset instead) - You need to transfer general files (use pilot-share instead) - You need real-time model inference results (use pilot-rpc instead)

ML model distribution with model cards, metadata, and version tracking.

Commands

Publish Model Availability

bash

pilotctl --json publish "$PEER" models --data '{"type":"model_available","name":"resnet50","version":"1.0.0","framework":"pytorch"}'

Request Model

bash

pilotctl --json send-message "$DEST" --data '{"type":"model_request","name":"resnet50","preferred_format":"onnx"}'

Send Model with Metadata

bash

pilotctl --json send-message "$DEST" --data '{"type":"model_metadata","name":"llama3_8b","file":{"checksum":"abc123"}}'
pilotctl --json send-file "$DEST" "$MODEL_FILE"

Validate Checksum

bash

EXPECTED_CHECKSUM=$(pilotctl --json inbox | jq -r '.messages[] | select(.type == "model_metadata") | .file.checksum' | head -1)
ACTUAL_CHECKSUM=$(md5sum "$RECEIVED_MODEL" | cut -d' ' -f1)
[ "$EXPECTED_CHECKSUM" = "$ACTUAL_CHECKSUM" ] && echo "Model verified"

Workflow Example

bash

#!/bin/bash
# Model distribution

PEER="agent-b"

share_model() {
  local model_file="$1"
  local model_name="${2:-$(basename $model_file .pth)}"

  pilotctl --json publish "$PEER" models --data "{\"type\":\"model_available\",\"name\":\"$model_name\"}"
}

share_model "model.pth" "my-model"

Dependencies

Requires pilot-protocol, pilotctl, jq, and md5sum.