lucidrains/bottleneck-transformer-pytorch
A PyTorch implementation of the Bottleneck Transformer architecture for visual recognition tasks, combining convolutional layers with self-attention mechanisms.
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This repository provides a PyTorch implementation of the Bottleneck Transformer (BoTNet), a vision transformer architecture that replaces spatial convolutions in ResNet blocks with multi-head self-attention. The model achieves better performance-compute trade-off than EfficientNet and DeiT on image classification tasks. It includes a BottleStack layer that can be integrated with ResNet backbones to create BotNet models, supporting configurable dimensions, heads, and relative positional embeddings.
Frequently asked
- What is lucidrains/bottleneck-transformer-pytorch?
- A PyTorch implementation of the Bottleneck Transformer architecture for visual recognition tasks, combining convolutional layers with self-attention mechanisms.
- Is bottleneck-transformer-pytorch open source?
- Yes — lucidrains/bottleneck-transformer-pytorch is open source, released under the MIT license.
- What language is bottleneck-transformer-pytorch written in?
- lucidrains/bottleneck-transformer-pytorch is primarily written in Python.
- How popular is bottleneck-transformer-pytorch?
- lucidrains/bottleneck-transformer-pytorch has 677 stars on GitHub.
- Where can I find bottleneck-transformer-pytorch?
- lucidrains/bottleneck-transformer-pytorch is on GitHub at https://github.com/lucidrains/bottleneck-transformer-pytorch.