RRepoGEO

REPOGEO REPORT · LITE

mlfoundations/open_flamingo

Default branch main · commit 655f693f · scanned 5/13/2026, 4:01:58 AM

GitHub: 4,096 stars · 319 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 mlfoundations/open_flamingo, 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's opening paragraph to clarify its specialized role

    Why:

    CURRENT
    Welcome to our open source implementation of DeepMind's Flamingo! In this repository, we provide a PyTorch implementation for training and evaluating OpenFlamingo models.
    COPY-PASTE FIX
    Welcome to OpenFlamingo, an open-source PyTorch framework for training and evaluating large multimodal models. This repository provides a robust implementation for building and experimenting with few-shot, in-context learning Vision-Language Models (VLMs) inspired by DeepMind's Flamingo.
  • mediumtopics#2
    Add more specific topics to highlight few-shot VLM training

    Why:

    CURRENT
    computer-vision, deep-learning, flamingo, in-context-learning, language-model, multimodal-learning, pytorch
    COPY-PASTE FIX
    computer-vision, deep-learning, flamingo, in-context-learning, language-model, multimodal-learning, pytorch, few-shot-learning, vision-language-models, vlm-framework
  • mediumcomparison#3
    Add a 'Comparison to Alternatives' section in the README

    Why:

    COPY-PASTE FIX
    Add a new section titled 'Comparison to Alternatives' or 'Why OpenFlamingo?' in the README, explicitly outlining how OpenFlamingo differs from and complements other popular ML frameworks (e.g., Hugging Face Transformers, PyTorch Lightning) and VLM projects (e.g., OpenCLIP) in terms of its focus on few-shot, in-context learning for Flamingo-style models.

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 mlfoundations/open_flamingo
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
huggingface/transformers
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. huggingface/transformers · recommended 1×
  2. huggingface/diffusers · recommended 1×
  3. huggingface/accelerate · recommended 1×
  4. Lightning-AI/lightning · recommended 1×
  5. tensorflow/tensorflow · recommended 1×
  • CATEGORY QUERY
    How can I train large models that understand both images and text effectively?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers (huggingface/transformers)
    2. 🤗 Diffusers (huggingface/diffusers)
    3. Accelerate (huggingface/accelerate)
    4. PyTorch Lightning (Lightning-AI/lightning)
    5. TensorFlow (tensorflow/tensorflow)
    6. Keras (keras-team/keras)
    7. DeepSpeed (microsoft/DeepSpeed)
    8. JAX (google/jax)
    9. Flax (google/flax)
    10. OpenAI CLIP
    11. DALL-E 2
    12. Stable Diffusion (Stability-AI/stablediffusion)
    13. Midjourney

    AI recommended 13 alternatives but never named mlfoundations/open_flamingo. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What framework facilitates in-context learning for vision-language models using PyTorch?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. PyTorch-Lightning
    3. OpenCLIP
    4. MMDetection/MMDetection3D/MMYOLO
    5. timm

    AI recommended 5 alternatives but never named mlfoundations/open_flamingo. 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 mlfoundations/open_flamingo?
    pass
    AI did not name mlfoundations/open_flamingo — 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 mlfoundations/open_flamingo in production, what risks or prerequisites should they evaluate first?
    pass
    AI named mlfoundations/open_flamingo 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 mlfoundations/open_flamingo solve, and who is the primary audience?
    pass
    AI named mlfoundations/open_flamingo explicitly

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

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  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
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