TacoSkill LAB
TacoSkill LAB
HomeSkillHubCreatePlaygroundSkillKit
© 2026 TacoSkill LAB
AboutPrivacyTerms
  1. Home
  2. /
  3. SkillHub
  4. /
  5. segment-anything-model
Improve

segment-anything-model

8.7

by davila7

115Favorites
277Upvotes
0Downvotes

Foundation model for image segmentation with zero-shot transfer. Use when you need to segment any object in images using points, boxes, or masks as prompts, or automatically generate all object masks in an image.

image segmentation

8.7

Rating

0

Installs

Machine Learning

Category

Quick Review

Exceptional skill documentation for the Segment Anything Model. The description is crystal clear about when to use SAM versus alternatives. Task knowledge is comprehensive with detailed code examples covering all major use cases (interactive segmentation, automatic mask generation, ONNX deployment, batch processing). Structure is excellent with clear sections, tables, and progressive complexity, though SKILL.md is quite long. Novelty is strong - SAM is a complex foundation model requiring specific prompting techniques and workflow understanding that would consume many tokens for a CLI agent to discover independently. Minor room for improvement in condensing the main file further by moving some workflows to referenced files.

LLM Signals

Description coverage10
Task knowledge10
Structure9
Novelty8

GitHub Signals

18,073
1,635
132
71
Last commit 0 days ago

Publisher

davila7

davila7

Skill Author

Related Skills

ml-pipelinesparse-autoencoder-traininghuggingface-accelerate

Loading SKILL.md…

Try onlineView on GitHub

Publisher

davila7 avatar
davila7

Skill Author

Related Skills

ml-pipeline

Jeffallan

6.4

sparse-autoencoder-training

zechenzhangAGI

7.6

huggingface-accelerate

zechenzhangAGI

7.6

moe-training

zechenzhangAGI

7.6
Try online