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Training Multimodal

nimapourjafar.com · 3,536 words · saved by 1 readers

TLDR: We achieve competitive results in multimodal AI using late fusion techniques, training an 8B parameter model on a single 8xH100 cluster, outperforming similar-sized open-source models across various benchmarks for less than $2000 We also test out an early fusion architecture and determine that while it initially underperforms compared to late fusion, it shows potential for richer cross-modal learning given more extensive training Want to just see our experimental code: check it out here! Want to start training your own model? Check out the Omega Labs subnet! Get paid (enough to cover compute) to train your own models I also have a bunch of multimodal datasets you can check out on Hugging Face exported to conversation formats I spent a good chunk of summer at Omega Labs helping them kickoff their experiments with multimodal artificial intelligence — from creating datasets, setting up training code, and doing the runs A big issue I found while doing this is the lack of resources an

Training Multimodal > Nima Pourjafar [ projects ] [ blog ] TLDR: We achieve competitive results in multimodal AI using late fusion techniques, training an 8B parameter model on a single 8xH100 cluster, outperforming similar-sized open-source models across various benchmarks for less than $2000 We also test out an early fusion architecture and determine that while it initially underperforms compared to late fusion, it shows potential for richer cross-modal learning given more extensive training Want to just see our experimental code: check it out here! Want to start training your own model? Che

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