kklemon/FlashPerceiver
Fast and memory efficient PyTorch implementation of the Perceiver with FlashAttention.
For machine learning engineers working with large and complex datasets, FlashPerceiver provides a highly efficient way to process data using Perceiver models. It takes your raw data, potentially with various input dimensions and masks, and processes it into compressed, meaningful representations or task-specific outputs, even for multi-task scenarios. This project is ideal for those who need to build or train deep learning models that can handle very long input sequences without prohibitive memory or speed costs.
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Use this if you are a machine learning engineer or researcher building Perceiver-based models and need significantly faster training times and reduced memory consumption when dealing with high-dimensional or long sequence data.
Not ideal if you are looking for a pre-trained model or a high-level API for non-machine learning tasks, as this is a foundational library for model implementation.
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Python
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Last pushed
Nov 04, 2024
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