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alpamayo-r1

Router for Alpamayo R1 multimodal driving inference and trajectory sampling.

中文简介正在准备中。当前显示原文说明。

查看安装方法

包含的文件(10)

  • SKILL.md2.3 KB
  • references/repo-provenance.md856 B
  • references/repo-routing-metadata.json332 B
  • references/troubleshooting.md2.5 KB
  • sub-skills/inference/references/api-reference.md4.0 KB
  • sub-skills/inference/references/data-formats.md3.6 KB
  • sub-skills/inference/references/troubleshooting.md4.7 KB
  • sub-skills/inference/references/workflows.md4.3 KB
  • sub-skills/inference/scripts/run_inference_smoke.py7.7 KB
  • sub-skills/inference/SKILL.md2.1 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Alpamayo R1

Use this skill for Alpamayo R1 inference on PhysicalAI-AV clips: load one clip, build the multimodal prompt, run the model on CUDA, inspect reasoning traces, and compare predicted trajectories to ground truth.

When to use this skill

  • The user wants to run Alpamayo R1 on a PhysicalAI-AV clip.
  • The user asks how to load the dataset, build the chat template, or sample future trajectories.
  • The user wants Chain-of-Causation text, minADE comparison, or notebook-style visualization.
  • The user needs help with gated HF resources, CUDA setup, or flash-attn / SDPA fallback behavior.

Install and verify

Use a Python 3.12 CUDA environment with the package dependencies installed, then perform a minimal import check from outside the checkout:

python -m pip install -e <repo-checkout>
python -I -c "import alpamayo_r1, torch; print(alpamayo_r1.__name__); print(torch.cuda.is_available())"

If the editable install or import fails, open references/troubleshooting.md before changing the workflow.

Route map

  • sub-skills/inference/SKILL.md — the end-to-end driving inference workflow, including dataset loading, prompt creation, model sampling, output interpretation, and the bundled smoke script.
  • references/repo-provenance.md — source commit, version, and evidence paths used to build this skill.
  • references/repo-routing-metadata.json — structured router metadata consumed during repo-skill import.
  • references/troubleshooting.md — cross-cutting install/import/backend guidance.

Shared notes

  • This repository exposes no public CLI entry point; use the Python API or the bundled smoke script from the inference sub-skill.
  • The primary workflow is CUDA-first. Flash-attn is the default attention path, but the inference sub-skill documents the SDPA fallback for compatibility issues.
  • Training, SFT, and RL post-training are out of scope for this skill.

Fastest path

  1. Read sub-skills/inference/SKILL.md.
  2. Use sub-skills/inference/scripts/run_inference_smoke.py for a runnable sample.
  3. If anything fails before the first clip loads, check references/troubleshooting.md.

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