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3 months ago
OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models

Abstract
We introduce OpenFlamingo, a family of autoregressive vision-language models ranging from 3B to 9B parameters. OpenFlamingo is an ongoing effort to produce an open-source replication of DeepMind's Flamingo models. On seven vision-language datasets, OpenFlamingo models average between 80 - 89% of corresponding Flamingo performance. This technical report describes our models, training data, hyperparameters, and evaluation suite. We share our models and code at https://github.com/mlfoundations/open_flamingo.
Code Repositories
luodian/otter
pytorch
Mentioned in GitHub
mlfoundations/open_flamingo
Official
pytorch
Mentioned in GitHub
Benchmarks
| Benchmark | Methodology | Metrics |
|---|---|---|
| visual-question-answering-on-mm-vet | OpenFlamingo-9B (LLaMA-7B) | GPT-4 score: 21.8±0.1 Params: 9B |
| visual-question-answering-on-mm-vet | OpenFlamingo-9B (MPT-7B) | GPT-4 score: 24.8±0.2 Params: 9B |
| visual-question-answering-on-mm-vet-v2 | OpenFlamingo-9B | GPT-4 score: 17.6±0.2 Params: 9B |
| visual-question-answering-vqa-on-core-mm | OpenFlamingo-v2 | Abductive: 5.3 Analogical: 1.11 Deductive: 8.88 Overall score: 6.82 Params: 9B |
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