RRepoGEO

REPOGEO REPORT · LITE

OFA-Sys/OFA

Default branch main · commit a36b91ce · scanned 6/20/2026, 4:32:53 PM

GitHub: 2,559 stars · 249 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
57 /100
Needs work
Category recall
1 / 2
Avg rank #5.0 when recommended
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 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 OFA-Sys/OFA, 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
    Explicitly state Chinese support for key multimodal tasks in README intro

    Why:

    CURRENT
    OFA is a unified sequence-to-sequence pretrained model (support **English** and **Chinese**) that unifies modalities (i.e., cross-modality, vision, language) and tasks (**finetuning** and **prompt tuning** are supported): image captioning (1st at the MSCOCO Leaderboard), VQA (link), visual grounding, text-to-image generation, text classification, text generation, image classification, etc.
    COPY-PASTE FIX
    OFA is a unified sequence-to-sequence pretrained model that unifies modalities (i.e., cross-modality, vision, language) and tasks, supporting both **English and Chinese**. It offers strong performance for tasks such as **Chinese and English image captioning** (1st at MSCOCO Leaderboard), VQA, visual grounding, and **Chinese and English text-to-image generation**, with both finetuning and prompt tuning supported.
  • mediumhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://huggingface.co/ofa-sys
  • lowreadme#3
    Add a concise 'Why OFA?' or 'Key Differentiator' section

    Why:

    COPY-PASTE FIX
    ## Why OFA? Our Core Differentiator
OFA stands out as a **unified sequence-to-sequence framework** designed to handle a wide spectrum of multimodal tasks (vision, language) and modalities within a single, efficient model architecture. This eliminates the need for separate models for different tasks, streamlining development and deployment.

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
1 / 2
50% of queries surface OFA-Sys/OFA
Avg rank
#5.0
Lower is better. #1 = top recommendation.
Share of voice
6%
Of all named tools, what % are you?
Top rival
BLIP-2
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. BLIP-2 · recommended 2×
  2. Flamingo · recommended 1×
  3. PaLI · recommended 1×
  4. CoCa · recommended 1×
  5. GIT · recommended 1×
  • CATEGORY QUERY
    Seeking a unified sequence-to-sequence model for various vision-language and multimodal tasks.
    you: #5
    AI recommended (in order):
    1. Flamingo
    2. PaLI
    3. BLIP-2
    4. CoCa
    5. OFA ← you
    6. GIT
    Show full AI answer
  • CATEGORY QUERY
    Which pretrained model supports Chinese for image captioning and text-to-image generation?
    you: not recommended
    AI recommended (in order):
    1. CogView2
    2. CogVideo
    3. Stable Diffusion
    4. DALL-E 2
    5. DALL-E 3
    6. BLIP-2
    7. InstructBLIP
    8. MiniGPT-4
    9. ERNIE-ViLG
    10. CLIP

    AI recommended 10 alternatives but never named OFA-Sys/OFA. 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 OFA-Sys/OFA?
    pass
    AI named OFA-Sys/OFA explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts OFA-Sys/OFA in production, what risks or prerequisites should they evaluate first?
    pass
    AI named OFA-Sys/OFA 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 OFA-Sys/OFA solve, and who is the primary audience?
    pass
    AI named OFA-Sys/OFA explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of OFA-Sys/OFA. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/OFA-Sys/OFA.svg)](https://repogeo.com/en/r/OFA-Sys/OFA)
HTML
<a href="https://repogeo.com/en/r/OFA-Sys/OFA"><img src="https://repogeo.com/badge/OFA-Sys/OFA.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

OFA-Sys/OFA — 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