Trending-skills llm-architecture-gallery

---
name: llm-architecture-gallery
description: Source data and metadata management for the LLM Architecture Gallery, a visual catalog of large language model architectures by Sebastian Raschka.
triggers:
  - add a model to the LLM architecture gallery
  - update models.yml for the architecture gallery
  - how do I contribute a new LLM architecture entry
  - edit the LLM gallery metadata
  - add image and metadata for a new language model
  - update model facts in the architecture gallery
  - how does the models.yml schema work
  - submit a new entry to rasbt llm architecture gallery
---

# LLM Architecture Gallery

> Skill by [ara.so](https://ara.so) — Daily 2026 Skills collection.

## What This Project Does

The [LLM Architecture Gallery](https://sebastianraschka.com/llm-architecture-gallery/) is a visual catalog of large language model architectures. This repository (`rasbt/llm-architecture-gallery`) is the **source data layer** — it contains the `models.yml` file that drives every gallery card: model names, architecture images, release dates, fact-sheet fields, and external links.

The live site reads from this repo. Contributing here means your model entry appears on the public gallery.

---

## Repository Structure

llm-architecture-gallery/ ├── models.yml # Primary data file — all model metadata └── images/ └── architectures/ # .webp architecture diagrams └── hero/ # Hero/banner images

---

## The `models.yml` Schema

Each top-level key is the **canonical model name** as it appears on the gallery card.

### Minimal Entry

```yaml
GPT-4o:
  image: "/llm-architecture-gallery/images/architectures/gpt-4o.webp"
  date: '2024-05-13'

Full Entry (all known fields)

DeepSeek R1:
  image: "/llm-architecture-gallery/images/architectures/deepseek-v3-r1-671-billion.webp"
  date: '2025-01-20'
  parameters: "671B"
  architecture: "Mixture of Experts (MoE)"
  context_length: "128K"
  organization: "DeepSeek"
  license: "MIT"
  paper: "https://arxiv.org/abs/2501.12948"
  code: "https://github.com/deepseek-ai/DeepSeek-R1"
  notes: "Reasoning model trained via reinforcement learning."

Field Reference

image

.webp

date

parameters

"7B"

"671B"

"1.5T"

architecture

"Transformer"

"MoE"

"SSM"

context_length

"128K"

"1M"

organization

license

paper

code

notes

Image URL Convention

Images are stored under

/llm-architecture-gallery/images/architectures/

.webp

To get a full public URL, prepend

https://sebastianraschka.com

# Stored path in models.yml:
/llm-architecture-gallery/images/architectures/deepseek-v3-r1-671-billion.webp

# Full public URL:
https://sebastianraschka.com/llm-architecture-gallery/images/architectures/deepseek-v3-r1-671-billion.webp

Naming convention for image files:

• lowercase, hyphen-separated
• include organization or model family when helpful
• suffix with parameter count if known
• always

  .webp

  format

Examples:

llama-3-70-billion.webp
mistral-7b.webp
deepseek-v3-r1-671-billion.webp
gemma-2-27b.webp

Adding a New Model Entry

Step 1 — Prepare the architecture image

Convert your diagram to

.webp

images/architectures/<model-slug>.webp

Recommended dimensions: ~1200×900px or similar landscape ratio.

Step 2 — Add entry to

models.yml

Open

models.yml

date

Llama 3.1 405B:
  image: "/llm-architecture-gallery/images/architectures/llama-3-1-405-billion.webp"
  date: '2024-07-23'
  parameters: "405B"
  architecture: "Transformer (GQA)"
  context_length: "128K"
  organization: "Meta"
  license: "Llama 3.1 Community License"
  paper: "https://arxiv.org/abs/2407.21783"
  code: "https://github.com/meta-llama/llama3"
  notes: "Flagship open-weights model from Meta's Llama 3.1 family."

Step 3 — Validate YAML syntax

# Python — validate the file parses without errors
python3 -c "
import yaml, sys
with open('models.yml') as f:
    data = yaml.safe_load(f)
print(f'OK: {len(data)} models loaded')
for name, meta in data.items():
    if 'image' not in meta:
        print(f'WARNING: {name!r} missing image field')
    if 'date' not in meta:
        print(f'WARNING: {name!r} missing date field')
"

Step 4 — Open a Pull Request

git checkout -b add-llama-3-1-405b
git add models.yml images/architectures/llama-3-1-405-billion.webp
git commit -m "Add Llama 3.1 405B entry"
git push origin add-llama-3-1-405b
# Then open PR at: https://github.com/rasbt/llm-architecture-gallery/pulls

Working with

models.yml

Programmatically

Python — load and query all entries

import yaml
from pathlib import Path
from datetime import date

with open("models.yml") as f:
    models = yaml.safe_load(f)

# List all models sorted by date
sorted_models = sorted(
    models.items(),
    key=lambda kv: kv[1].get("date", "1900-01-01")
)

for name, meta in sorted_models:
    print(f"{meta.get('date', 'unknown')}  {name}  [{meta.get('parameters', '?')}]")

Python — find all MoE models

import yaml

with open("models.yml") as f:
    models = yaml.safe_load(f)

moe_models = {
    name: meta
    for name, meta in models.items()
    if "moe" in meta.get("architecture", "").lower()
    or "mixture" in meta.get("architecture", "").lower()
}

for name, meta in moe_models.items():
    print(f"{name}: {meta.get('architecture')} — {meta.get('parameters', '?')}")

Python — generate a Markdown index

import yaml

with open("models.yml") as f:
    models = yaml.safe_load(f)

BASE_URL = "https://sebastianraschka.com"

lines = ["# Model Index\n"]
for name, meta in sorted(models.items(), key=lambda kv: kv[1].get("date", "")):
    img_url = BASE_URL + meta["image"]
    paper = meta.get("paper", "")
    date = meta.get("date", "")
    params = meta.get("parameters", "")
    org = meta.get("organization", "")
    line = f"- **{name}** ({date}) {org} {params}"
    if paper:
        line += f" — [paper]({paper})"
    lines.append(line)

print("\n".join(lines))

Python — add a new model entry programmatically

import yaml
from collections import OrderedDict

NEW_MODEL = {
    "Phi-4": {
        "image": "/llm-architecture-gallery/images/architectures/phi-4-14b.webp",
        "date": "2024-12-12",
        "parameters": "14B",
        "architecture": "Transformer",
        "context_length": "16K",
        "organization": "Microsoft",
        "license": "MIT",
        "paper": "https://arxiv.org/abs/2412.08905",
        "code": "https://huggingface.co/microsoft/phi-4",
        "notes": "Small language model emphasizing reasoning and STEM."
    }
}

with open("models.yml") as f:
    models = yaml.safe_load(f)

models.update(NEW_MODEL)

with open("models.yml", "w") as f:
    yaml.dump(models, f, allow_unicode=True, sort_keys=False, default_flow_style=False)

print(f"Written. Total models: {len(models)}")

Common Patterns

Check for missing required fields across all entries

import yaml

REQUIRED = {"image", "date"}

with open("models.yml") as f:
    models = yaml.safe_load(f)

issues = []
for name, meta in models.items():
    for field in REQUIRED:
        if field not in meta:
            issues.append(f"  {name!r}: missing '{field}'")

if issues:
    print("Validation errors:")
    print("\n".join(issues))
else:
    print(f"All {len(models)} entries valid.")

List all unique organizations

import yaml

with open("models.yml") as f:
    models = yaml.safe_load(f)

orgs = sorted({m.get("organization", "Unknown") for m in models.values()})
for org in orgs:
    print(org)

Count models by architecture family

import yaml
from collections import Counter

with open("models.yml") as f:
    models = yaml.safe_load(f)

arch_counts = Counter(
    m.get("architecture", "Unknown").split("(")[0].strip()
    for m in models.values()
)

for arch, count in arch_counts.most_common():
    print(f"{count:3d}  {arch}")

Troubleshooting

YAML parse errors

# Quick check with Python
python3 -c "import yaml; yaml.safe_load(open('models.yml'))"

# Or install yamllint for detailed feedback
pip install yamllint
yamllint models.yml

Common causes:

• Unquoted strings containing

  :

  — wrap in quotes:

  "Transformer: GQA"

• Inconsistent indentation (mix of tabs and spaces)
• Missing quotes around dates that look like floats: use

  '2024-01-01'

  not

  2024-01-01

Image path not resolving on the live site

Ensure the path starts with

/llm-architecture-gallery/images/architectures/

https://sebastianraschka.com

# ✅ Correct
image: "/llm-architecture-gallery/images/architectures/my-model.webp"

# ❌ Wrong — bare filename
image: "my-model.webp"

# ❌ Wrong — full URL
image: "https://sebastianraschka.com/llm-architecture-gallery/images/architectures/my-model.webp"

Date field format

Always quote dates to avoid YAML parsing them as

datetime

# ✅ Correct — quoted string
date: '2025-01-20'

# ⚠️ Risky — may parse as datetime depending on YAML loader
date: 2025-01-20

Quick Reference

models.yml

.webp

images/architectures/

https://sebastianraschka.com

image

python3 -c "import yaml; yaml.safe_load(open('models.yml'))"

models.yml