RRepoGEO

REPOGEO REPORT · LITE

Quentin-Anthony/torch-profiling-tutorial

Default branch main · commit 97a9408f · scanned 6/13/2026, 3:48:09 PM

GitHub: 577 stars · 32 forks

AI VISIBILITY SCORE
10 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
0 / 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 Quentin-Anthony/torch-profiling-tutorial, 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

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

OVERALL DIRECTION
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    A practical tutorial for PyTorch developers and researchers on using profiling tools like PyTorch Profiler, NVIDIA NSYS, and AMD Rocprof to identify and optimize deep learning model performance bottlenecks.
  • mediumreadme#2
    Add a concise introductory paragraph to the README

    Why:

    CURRENT
    # How to Profile Models in PyTorch
By Quentin Anthony

## Table of Contents
    COPY-PASTE FIX
    # How to Profile Models in PyTorch

This repository provides a comprehensive, hands-on tutorial for PyTorch developers to master profiling techniques. Learn to identify and resolve performance bottlenecks in deep learning models using PyTorch Profiler, NVIDIA NSYS, and AMD Rocprof.

By Quentin Anthony

## Table of Contents

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 Quentin-Anthony/torch-profiling-tutorial
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch Profiler
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch Profiler · recommended 2×
  2. TensorFlow Profiler · recommended 2×
  3. NVIDIA Nsight Systems · recommended 2×
  4. cProfile · recommended 1×
  5. jiffyclub/snakeviz · recommended 1×
  • CATEGORY QUERY
    How can I identify performance bottlenecks in my deep learning model training?
    you: not recommended
    AI recommended (in order):
    1. PyTorch Profiler
    2. TensorFlow Profiler
    3. NVIDIA Nsight Systems
    4. cProfile
    5. snakeviz (jiffyclub/snakeviz)
    6. perf
    7. Intel VTune Profiler

    AI recommended 7 alternatives but never named Quentin-Anthony/torch-profiling-tutorial. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are effective methods for understanding GPU efficiency when training neural networks?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA Nsight Systems
    2. NVIDIA Nsight Compute
    3. nvidia-smi
    4. PyTorch Profiler
    5. TensorFlow Profiler
    6. nvprof
    7. htop
    8. atop

    AI recommended 8 alternatives but never named Quentin-Anthony/torch-profiling-tutorial. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 Quentin-Anthony/torch-profiling-tutorial?
    pass
    AI did not name Quentin-Anthony/torch-profiling-tutorial — 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?

  • If a team adopts Quentin-Anthony/torch-profiling-tutorial in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name Quentin-Anthony/torch-profiling-tutorial — 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?

  • In one sentence, what problem does the repo Quentin-Anthony/torch-profiling-tutorial solve, and who is the primary audience?
    pass
    AI did not name Quentin-Anthony/torch-profiling-tutorial — 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?

Embed your GEO score

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Quentin-Anthony/torch-profiling-tutorial — 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