flamingo-pytorch
performer-pytorch
flamingo-pytorch | performer-pytorch | |
---|---|---|
3 | 2 | |
1,203 | 1,088 | |
- | - | |
0.0 | 1.8 | |
about 2 years ago | almost 3 years ago | |
Python | Python | |
MIT License | MIT License |
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flamingo-pytorch
- flamingo tackling visual understanding
- GitHub - lucidrains/flamingo-pytorch: Implementation of Flamingo, state-of-the-art few-shot visual question answering attention net out of Deepmind, in Pytorch
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[R] Flamingo: a Visual Language Model for Few-Shot Learning (from DeepMind)
code, for anyone interested https://github.com/lucidrains/flamingo-pytorch
performer-pytorch
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[R] Rotary Positional Embeddings - a new relative positional embedding for Transformers that significantly improves convergence (20-30%) and works for both regular and efficient attention
Performer is the best linear attention variant, but linear attention is just one type of efficient attention solution. I have rotary embeddings already in the repo https://github.com/lucidrains/performer-pytorch and you can witness this phenomenon yourself by toggling it on / off
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Why has Google's Performer model not replaced traditional softmax attention?
Here's an PyTorch implementation if you want to play around with it: lucidrains/performer-pytorch: An implementation of Performer, a linear attention-based transformer, in Pytorch (github.com)
What are some alternatives?
x-transformers - A concise but complete full-attention transformer with a set of promising experimental features from various papers
long-range-arena - Long Range Arena for Benchmarking Efficient Transformers
soundstorm-pytorch - Implementation of SoundStorm, Efficient Parallel Audio Generation from Google Deepmind, in Pytorch
Perceiver - Implementation of Perceiver, General Perception with Iterative Attention in TensorFlow
DALLE-pytorch - Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
memory-efficient-attention-pytorch - Implementation of a memory efficient multi-head attention as proposed in the paper, "Self-attention Does Not Need O(n²) Memory"
nuwa-pytorch - Implementation of NÃœWA, state of the art attention network for text to video synthesis, in Pytorch
reformer-pytorch - Reformer, the efficient Transformer, in Pytorch
slot-attention - Implementation of Slot Attention from GoogleAI
vit-pytorch - Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
spin-model-transformers - Physics-inspired transformer modules based on mean-field dynamics of vector-spin models in JAX
deep-implicit-attention - Implementation of deep implicit attention in PyTorch