![[Long Review] Fully Sharded Data Parallel: faster AI training with fewer GPUs](/media/video/2022/04/long-review-fully-sharded-data-parallel-faster-ai-training-with-fewer-gpus/preview.jpg)
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[Long Review] Fully Sharded Data Parallel: faster AI training with fewer GPUs
Training a billion-parameter speech or language model on a modest GPU budget used to mean picking your poison across pipeline parallelism, tensor parallelism, …
![[Short Review] Fully Sharded Data Parallel: faster AI training with fewer GPUs](/media/video/2022/04/short-review-fully-sharded-data-parallel-faster-ai-training-with-fewer-gpus/preview.jpg)
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[Short Review] Fully Sharded Data Parallel: faster AI training with fewer GPUs
Fully Sharded Data Parallel is Meta's answer to a question every speech and language team eventually asks: how do we train models an order of magnitude bigger …
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From Breaking Bad to Wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations
What do Walter White, Jesse Pinkman, and a batch of unlabeled audio have in common?
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Exploring Wav2vec 2.0 fine-tuning for improved speech emotion recognition
Speech emotion recognition has long been stuck with tiny labeled datasets and hand-crafted acoustic features.