tao-finetune-video-clip SKILL.md skillA
tao-finetune-video-clip from nvidia-tao/tao-skill-bank is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add nvidia-tao/tao-skill-bank/tao-finetune-video-clip@v0.1.0Pins v0.1.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- nvidia-tao/tao-skill-bank
- Path
skills/models/tao-finetune-video-clip/SKILL.md- Versions recorded
- 5
- Latest version
- v0.1.0, committed Oct 15, 2026
- First version recorded
- Aug 5, 2026
- Size
- 13,959 bytes
- Repository stars
- 95
- License
- Apache-2.0
InternVideo2-CLIP L14 (TAO video_clip) for video-text retrieval, zero-shot classification, embedding extraction, LoRA fine-tuning, ONNX export, and TensorRT deployment. Use when the user asks to "fine-tune IV2CLIP", "run video_clip train/evaluate/inference/export", "build a Video-CLIP TensorRT engine", "InternVideo2-CLIP on KPI chunks", or "TAO video_clip on vadr1_chunks JSON".
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# InternVideo2-CLIP (TAO video_clip) > **Standalone install?** If this session was not initialized by the TAO skill bank plugin, run the `tao-setup` skill first (host preflight, credentials, cross-skill discovery). TAO task **`video_clip`** wraps OpenGVLab **InternVideo2-CLIP L14**. The PyTorch image provides `train`, `evaluate`, `inference`, `export`, and `default_specs`. TAO Deploy provides `gen_trt_engine`, TensorRT `evaluate`, and TensorRT `inference`. Container images and per-action commands are in `references/skill_info.yaml` and `references/tao-deploy-video-clip.skill_info.yaml`. Starting specs are in `references/spec_template_*.yaml`. > **Release note:** The pinned PyTorch image is the TAO 7.2 release-candidate build validated for Video-CLIP. It includes PyAV 17.1.0 as the primary decoder and ONNXScript 0.7.1 for export, with decord absent. The TAO Deploy image is pinned independently because `gen_trt_engine` and TensorRT-backed actions do not run in the PyTorch image. > …
Read the whole file at its exact version.
How to install
mdr add nvidia-tao/tao-skill-bank/tao-finetune-video-clip@sha256:39110badaeb25ab3The line at the top of this page pins the label v0.1.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_w4xargnrokqyuozk)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 5 versions of this file, between Aug 5, 2026 and Oct 15, 2026, about one every 18 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v0.1.0 latest | 2026-10-15 | f1e6f8d | 13,959 B | A | view · diff |
| v0.1.0 | 2026-09-22 | a924085 | 14,016 B | A | view · diff |
| v0.1.0 | 2026-08-29 | 7657a93 | 14,141 B | A | view · diff |
| v0.1.0 | 2026-08-11 | 115ac6d | 12,207 B | A | view · diff |
| v0.1.0 | 2026-08-05 | ae5e99c | 12,181 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (13959 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
nvidia-tao/tao-skill-bank · 95 stars · license Apache-2.0 · pushed 2026-10-21 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_w4xargnrokqyuozk GET https://markdownregistry.com/api/v1/resolve?ref=nvidia-tao/tao-skill-bank/tao-finetune-video-clip GET https://markdownregistry.com/api/v1/blob/39110badaeb25ab39d4e8037891322cf85848fd90cd6581702c5c49863b4107c
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.