Flamingo MLLM
[Deepmind](https://texonom.com/deepmind-5eb171c77b344d4786a9a5b23ae70eca) [open_flamingo](https://github.com/mlfoundations/open_flamingo) 


[Cross Validation](https://texonom.com/cross-validation-184e7cfc80d6410188922d27ef4ef52c) 과 self-attention layer를 번갈아 가며 적용해서 적은 양의 학습 데이터로부터도 효과적으로 정보를 추출
[Meta Learning](https://texonom.com/meta-learning-96b4df900e3d42c8b5c088f1eda778d6) 구조도 그래서 넣은거
그래서 [Few shot learning](https://texonom.com/fewshot-learning-f2a97adcbc774f4abd677a6db974329d) 에 좋은것





> [Untitled](https://storage.googleapis.com/deepmind-media/DeepMind.com/Blog/tackling-multiple-tasks-with-a-single-visual-language-model/flamingo.pdf)

> [Tackling multiple tasks with a single visual language model](https://www.deepmind.com/blog/tackling-multiple-tasks-with-a-single-visual-language-model?fbclid=IwAR0ToGRwuXzzPAKfKSbtAZ26OIDPHfoAGCoSzenyWXUfuHb_iLMjxa1Iw10)




