Skip to content
Back to skills

Inference

ASecurity

"End-to-end Alpamayo R1 multimodal driving inference, sample

  • 247 stars
  • 0 votes
  • 0 copies
  • 1 view
  • Added September 8, 2026
datagoapi

Works with

  • cli
  • api

Security analysis

A100/100

Pro scans all 6 files and shows the line behind each finding

Scanned September 8, 2026

npx -y skills add VectorSpaceLab/AREX-Skill --skill inference --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Inference?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Inference
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/vectorspacelab-inference/badge)](https://www.skillsdirectory.com/skills/vectorspacelab-inference)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: inference
description: "End-to-end Alpamayo R1 multimodal driving inference, sample
  generation, and troubleshooting."
metadata:
  disco-role: operating
disable-model-invocation: true
license: Apache 2.0
---

# Alpamayo R1 Inference

Use this sub-skill when the user wants to run, inspect, or adapt the Alpamayo R1 inference path on a PhysicalAI-AV clip.

## What this covers

- Load a gated PhysicalAI-AV clip and egomotion history/future.
- Build the multimodal chat prompt from stacked camera frames.
- Load `nvidia/Alpamayo-R1-10B` on CUDA with the Alpamayo tokenizer and processor.
- Sample future trajectories plus Chain-of-Causation text traces.
- Compare predicted trajectories with ground truth and visualize them in notebook style.
- Troubleshoot HF gating, CUDA OOM, flash-attn / SDPA fallback, device placement, prompt rank, and early `t0_us` failures.

## What this does not cover

- Training, SFT, RL post-training, or repo maintenance.
- Import/export plumbing or package provenance.
- Any workflow that depends on the original checkout at runtime.

## Fast route

1. Read `references/api-reference.md` for the public call contract.
2. Read `references/data-formats.md` for shapes, frames, and output semantics.
3. Follow `references/workflows.md` for the end-to-end inference flow and notebook-style visualization.
4. If anything fails, open `references/troubleshooting.md`.
5. Run `scripts/run_inference_smoke.py` as the bundled smoke test.

## Key defaults

- Default model id: `nvidia/Alpamayo-R1-10B`
- Default loader history / future / camera settings: 16 steps, 64 steps, 4 cameras
- Default attention path: `flash_attention_2`
- SDPA is a fallback for flash-attn incompatibility, not a replacement for the CUDA path.

## See also

- `../../SKILL.md` for the root router
- `../../references/repo-provenance.md`
- `../../references/repo-routing-metadata.json`
- `../../references/troubleshooting.md` for shared Alpamayo R1 troubleshooting
- `references/api-reference.md`
- `references/data-formats.md`
- `references/workflows.md`
- `references/troubleshooting.md`
- `scripts/run_inference_smoke.py`

Files in this skill

  • SKILL.md2.1 KB
  • references/api-reference.md4 KB
  • references/data-formats.md3.6 KB
  • references/troubleshooting.md4.7 KB
  • references/workflows.md4.3 KB
  • scripts/run_inference_smoke.py7.7 KB

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.