---

name: local-inference description: "Run or adapt local Skywork-R1V3 inference commands with safe Transformers/vLLM guidance." disable-model-invocation: true metadata: disco-role: operating license: MIT

Local Skywork-R1V3 inference

Use this sub-skill when a user wants to run, adapt, or debug local Skywork-R1V3 multimodal inference with either the Transformers entrypoint or the vLLM entrypoint.

Do not use this sub-skill for Skywork-R1V4 API batch testing; route that workflow to r1v4-api-testing. Do not use it for VLMEvalKit, EMMA, MMK12, or benchmark reproduction; route those workflows to evaluation-reproduction.

Operating posture

• Treat full Skywork-R1V3-38B inference as a heavy CUDA workflow. The safe helpers in this subtree do not load models, download checkpoints, initialize vLLM, import torch, or touch GPUs.
• Default model identity for local inference is Skywork/Skywork-R1V3-38B; allow a local checkpoint path or compatible model id when the user has already prepared weights.
• Confirm the backend first: Transformers for direct model.chat() behavior and explicit image patch lists; vLLM for tensor-parallel generation using chat templates.
• Confirm image count and prompt tags before running. Multi-image prompts need one image token per image unless the backend helper already adds them.
• Be explicit that native full-run verification is optional/unexecuted unless the user supplies model weights, CUDA dependencies, GPUs, and runtime budget.

Fast routing checklist

1. Need a command without loading the model? Use scripts/build_inference_command.py.
2. Need to estimate image tiling/patch pressure without torch? Use scripts/check_image_grid.py.
3. Need command and setup details? Read references/workflows.md.
4. Need exact flags and defaults? Read references/api-and-parameters.md.
5. Hit CUDA, model-loading, vLLM, image-tag, or OOM errors? Read references/troubleshooting.md.

Minimal safe helper examples

python scripts/build_inference_command.py --backend transformers \
  --image-path demo.png \
  --question "Describe the image and reason step by step."

python scripts/check_image_grid.py --width 1600 --height 900 --thumbnail

The generated command is only a command string for the user to run in their prepared inference environment; it is not executed by the helper.