We believe that our results and findings can help, shape, and facilitate future research in foundational, large-scale pretraining.
Image restoration techniques such as image super-resolution (SR), image denoising, and JPEG compression artefact reduction strive to recreate a high-quality clean image from a low-quality degraded image.
The key is that 1T was never ‘trained to convergence.’
MT-NLG has 3x the number of parameters compared to the existing largest models – GPT-3, Turing NLG, Megatron-LM and others.
PLATO-XL is trained on a high-performance GPU cluster with 256 NVIDIA Tesla V100 32G GPU cards.
Switch Transformer models were pretrained utilising 32 TPUs on the Colossal Clean Crawled Corpus, a 750 GB dataset composed of text snippets from Wikipedia, Reddit and others
Google has developed and benchmarked Switch Transformers, a technique to train language models, with over a trillion parameters. The research team said the 1.6 trillion parameter model is the largest
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