ai-for-science-ankh-ascend-npu-skill

ai-for-science-ankh-ascend-npu-skill is a skill for Claude Code from ascend-ai-coding/awesome-ascend-skills. It costs 100 tokens per session (3,532 once invoked), scanned A, original, no licence file.

A migration guide for running Ankh protein language models on Huawei Ascend NPU hardware. It covers environment checks, code changes, model-weight loading, validation scripts, and recording the setup.

In plain words
What is it for?
It is for adapting Ankh and similar Hugging Face Transformers and PyTorch protein models, loading their weights, and verifying their results on Ascend.
Why use it?
It addresses the work needed to move Ankh models from CUDA or other GPU setups to Ascend and confirm that they still load and run correctly.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the ascend-ai-for-science plugin — 14 skills shipped together , and of ai-for-science

Good fit It is for adapting Ankh and similar Hugging Face Transformers and PyTorch protein models, loading their weights, and verifying their results on Ascend.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ascend-ai-coding/awesome-ascend-skills/ankh
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add ascend-ai-coding/awesome-ascend-skills --skill ankh
Clone the repo
git clone --depth 1 https://github.com/ascend-ai-coding/awesome-ascend-skills

Made for: Claude Code.

Or install ascend-ai-for-science, the plugin that ships this one along with the rest of its 14 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ai-for-science-ankh-ascend-npu-skill

README.md
[![agentmods](https://agentmods.dev/badge/skills/ascend-ai-coding/awesome-ascend-skills/ankh/github.svg)](https://agentmods.dev/skills/ascend-ai-coding/awesome-ascend-skills/ankh)
Your own site
<a href="https://agentmods.dev/skills/ascend-ai-coding/awesome-ascend-skills/ankh"><img src="https://agentmods.dev/badge/skills/ascend-ai-coding/awesome-ascend-skills/ankh/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ai-for-science-ankh-ascend-npu-skill

Your own site · 80×15
<a href="https://agentmods.dev/skills/ascend-ai-coding/awesome-ascend-skills/ankh"><img src="https://agentmods.dev/badge/skills/ascend-ai-coding/awesome-ascend-skills/ankh.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 100 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,532 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00100 $0.03532
Opus 5 $0.00050 $0.01766
Sonnet 5 $0.00020 $0.00706
Haiku 4.5 $0.00010 $0.00353

Measured 7d ago against content hash e715a2b3f54c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

ai-for-science-ankh-ascend-npu-skill scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/verify_ankh_base_npu.py, scripts/verify_ankh_large_npu.py, scripts/verify_ankh3_large_npu.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/ai-for-science/models/ankh/SKILL.md · 399 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago First seen · 399 lines · 100 tokens per session scan A e715a2b3f54c

Subscribe to this mod's changes

ai-for-science-ankh-ascend-npu-skill is a skill published in the GitHub repository ascend-ai-coding/awesome-ascend-skills (168 stars, last pushed yesterday), with no licence file. It adds 100 tokens to every session and 3,532 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.

Related

Other skills, from other repositories

fine-tuning-serving-openpi

Fine-tune and serve Physical Intelligence OpenPI models (pi0, pi0-fast, pi0.5) using JAX or PyTorch backends for robot policy inference across ALOHA, DROID, and LIBERO environments. Use when adapting pi0 models to custom datasets, converting JAX checkpoints to PyTorch, running policy inference servers, or debugging…

Orchestra-Research/AI-Research-SKILLs · 87 tokens

huggingface-transformers

Use Hugging Face Transformers pipelines, tokenizers, and AutoModel interfaces for inference and fine-tuning workflows.

alivirgo/Major-AI-Skills · 28 tokens

neuroskill-bci

Use live BCI cognitive and mood state from NeuroSkill.

NousResearch/hermes-agent · 18 tokens

ruview-applications

Run RuView sensing applications — presence/occupancy, breathing & heart rate, activity & fall detection, 17-keypoint pose estimation (WiFlow), sleep monitoring & apnea screening, environment mapping, Mass Casualty Assessment (MAT), and the 3D point-cloud fusion demo. Use when someone wants to actually do something…

ruvnet/RuView · 79 tokens

pylabrobot

Develop and review PyLabRobot lab-automation resources, liquid-handling plans, offline simulations, and supported-device integrations. Use for PyLabRobot protocols or API questions; keep physical execution behind an explicit operator safety gate.

K-Dense-AI/scientific-agent-skills · 49 tokens

calibrate-room

Run the ADR-151 per-room calibration pipeline — baseline → enroll → extract → train → a bank of small specialists (presence/posture/breathing/heartbeat/restlessness/anomaly).

ruvnet/RuView · 41 tokens