REPOGEO REPORT · LITE

rasbt/LLM-workshop-2024

Default branch main · commit cf929412 · scanned 5/14/2026, 10:22:37 PM

GitHub: 1,092 stars · 378 forks

AI VISIBILITY SCORE

28 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

2 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface rasbt/LLM-workshop-2024, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

highreadme#1

Reposition the README H1 to explicitly state 'workshop' or 'tutorial'

Why:

CURRENT

# Pretraining and Finetuning LLMs from the Ground Up

COPY-PASTE FIX

# LLM Workshop 2024: Pretraining and Finetuning LLMs from the Ground Up (Code-First Tutorial)

hightopics#2
Add specific topics to clarify the repo's educational nature
Why:
CURRENT
```
large-language-models, llm, pytorch
```
COPY-PASTE FIX
```
large-language-models, llm, pytorch, workshop, tutorial, education, hands-on
```
mediumhomepage#3
Add the primary workshop environment link as the repository homepage
Why:
COPY-PASTE FIX
```
https://lightning.ai/lightning-ai/studios/llms-from-the-ground-up-workshop
```

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface rasbt/LLM-workshop-2024

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

PyTorch

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

PyTorch · recommended 1×
Transformers · recommended 1×
accelerate · recommended 1×
torch.distributed · recommended 1×
einops · recommended 1×

CATEGORY QUERY
How to implement large language models from the ground up using PyTorch?
you: not recommended
AI recommended (in order):
1. PyTorch
2. Transformers
3. accelerate
4. torch.distributed
5. einops
6. FlashAttention
7. xFormers
8. tensorboard
AI recommended 8 alternatives but never named rasbt/LLM-workshop-2024. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Resources for understanding LLM core architecture and practical finetuning techniques?
you: not recommended
AI recommended (in order):
1. The Illustrated Transformer
2. Hugging Face Transformers Library (huggingface/transformers)
3. Stanford CS224N
4. Attention Is All You Need
5. Hugging Face PEFT library (huggingface/peft)
6. Fast.ai's Practical Deep Learning for Coders
7. OpenAI API
AI recommended 7 alternatives but never named rasbt/LLM-workshop-2024. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
warn
Suggestion:
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of rasbt/LLM-workshop-2024?
pass
AI named rasbt/LLM-workshop-2024 explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts rasbt/LLM-workshop-2024 in production, what risks or prerequisites should they evaluate first?
pass
AI named rasbt/LLM-workshop-2024 explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo rasbt/LLM-workshop-2024 solve, and who is the primary audience?
pass
AI did not name rasbt/LLM-workshop-2024 — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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MARKDOWN (README)

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rasbt/LLM-workshop-2024 — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite