segment-anything-model SKILL.md skillA

segment-anything-model from orchestra-research/ai-research-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add orchestra-research/ai-research-skills/segment-anything-model@v1.0.0

Pins v1.0.0 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
orchestra-research/ai-research-skills
Path
18-multimodal/segment-anything/SKILL.md
Versions recorded
1
Latest version
v1.0.0, committed Nov 25, 2025
Size
13,403 bytes
Repository stars
13,718
License
MIT

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.

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

# Segment Anything Model (SAM)

Comprehensive guide to using Meta AI's Segment Anything Model for zero-shot image segmentation.

## When to use SAM

**Use SAM when:**
- Need to segment any object in images without task-specific training
- Building interactive annotation tools with point/box prompts
- Generating training data for other vision models
- Need zero-shot transfer to new image domains
- Building object detection/segmentation pipelines
- Processing medical, satellite, or domain-specific images

**Key features:**
- **Zero-shot segmentation**: Works on any image domain without fine-tuning
- **Flexible prompts**: Points, bounding boxes, or previous masks
- **Automatic segmentation**: Generate all object masks automatically
- **High quality**: Trained on 1.1 billion masks from 11 million images
- **Multiple model sizes**: ViT-B (fastest), ViT-L, ViT-H (most accurate)
- **ONNX export**: Deploy in browsers and edge devices

**Use alternatives instead:**
- **YOLO/Detectron2**: For real-time object detection with classes
- **Mask2Former**: For semantic/panoptic segmentation with categories
- **GroundingDINO + SAM**: For text-prompted segmentation
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add orchestra-research/ai-research-skills/segment-anything-model@sha256:6ac5c2f96cf7d0ae

The line at the top of this page pins the label v1.0.0, 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.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_qeykulyaaoyoqtnk.svg)](https://markdownregistry.com/a/art_qeykulyaaoyoqtnk)

1 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 1 version of this file, committed on Nov 25, 2025.

versioncommittedcommitsizeaudit
v1.0.0 latest2025-11-25 c4c0e5b 13,403 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (13403 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

GitHub

orchestra-research/ai-research-skills · 13,718 stars · license MIT · pushed 2026-10-11 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_qeykulyaaoyoqtnk
GET https://markdownregistry.com/api/v1/resolve?ref=orchestra-research/ai-research-skills/segment-anything-model
GET https://markdownregistry.com/api/v1/blob/6ac5c2f96cf7d0ae5f787164678701266930129aa06cc21818f20f77dacb6a71

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.

More from orchestra-research/ai-research-skills

autoresearch SKILL.md skill
orchestra-research/ai-research-skills · 0-autoresearch-skill/SKILL.md · Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid…
v1.0.0 · audit A · 13,718 stars
implementing-llms-litgpt SKILL.md skill
orchestra-research/ai-research-skills · 01-model-architecture/litgpt/SKILL.md · Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen…
v1.0.0 · audit A · 13,718 stars
mamba-architecture SKILL.md skill
orchestra-research/ai-research-skills · 01-model-architecture/mamba/SKILL.md · State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV…
v1.0.0 · audit A · 13,718 stars
nanogpt SKILL.md skill
orchestra-research/ai-research-skills · 01-model-architecture/nanogpt/SKILL.md · Educational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning…
v1.0.0 · audit A · 13,718 stars
rwkv-architecture SKILL.md skill
orchestra-research/ai-research-skills · 01-model-architecture/rwkv/SKILL.md · RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel)…
v1.0.0 · audit A · 13,718 stars
distributed-llm-pretraining-torchtitan SKILL.md skill
orchestra-research/ai-research-skills · 01-model-architecture/torchtitan/SKILL.md · Provides PyTorch-native distributed LLM pretraining using torchtitan with 4D parallelism (FSDP2, TP, PP, CP). Use when…
v1.0.0 · audit A · 13,718 stars
huggingface-tokenizers SKILL.md skill
orchestra-research/ai-research-skills · 02-tokenization/huggingface-tokenizers/SKILL.md · Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports…
v1.0.0 · audit A · 13,718 stars
sentencepiece SKILL.md skill
orchestra-research/ai-research-skills · 02-tokenization/sentencepiece/SKILL.md · Language-independent tokenizer treating text as raw Unicode. Supports BPE and Unigram algorithms. Fast (50k…
v1.0.0 · audit A · 13,718 stars
axolotl SKILL.md skill
orchestra-research/ai-research-skills · 03-fine-tuning/axolotl/SKILL.md · Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO…
v1.0.0 · audit A · 13,718 stars
llama-factory SKILL.md skill
orchestra-research/ai-research-skills · 03-fine-tuning/llama-factory/SKILL.md · Expert guidance for fine-tuning LLMs with LLaMA-Factory - WebUI no-code, 100+ models, 2/3/4/5/6/8-bit QLoRA, multimodal…
v1.0.0 · audit A · 13,718 stars
peft-fine-tuning SKILL.md skill
orchestra-research/ai-research-skills · 03-fine-tuning/peft/SKILL.md · Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B)…
v1.0.0 · audit A · 13,718 stars
unsloth SKILL.md skill
orchestra-research/ai-research-skills · 03-fine-tuning/unsloth/SKILL.md · Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization
v1.0.0 · audit A · 13,718 stars

Every file in orchestra-research/ai-research-skills

Browse by kind, by grade A, or by owner.