ml-cvnets
EfficientFormer
| ml-cvnets | EfficientFormer | |
|---|---|---|
| 4 | 2 | |
| 1,681 | 943 | |
| 1.4% | 0.6% | |
| 4.8 | 3.3 | |
| 6 months ago | 9 months ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ml-cvnets
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Apple Researchers Introduce ByteFormer: An AI Model That Consumes Only Bytes And Does Not Explicitly Model The Input Modality - MarkTechPost
https://github.com/apple/ml-cvnets/tree/main/examples/byteformer - Where the code will be located once uploaded
- CVNets - A library for training computer vision networks
- CVNets – A library for training computer vision networks
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Apple ML Researchers Introduce ‘MobileViT’: A Light-Weight And General-Purpose Vision Transformer For Mobile Devices
Github: https://github.com/apple/ml-cvnets
EfficientFormer
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A look at Apple’s new Transformer-powered predictive text model
I'm pretty fatigued on constantly providing references and sources in this thread but an example of what they've made availably publicly:
https://github.com/snap-research/EfficientFormer
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Snap and Northeastern University Researchers Propose EfficientFormer: A Vision Transformer That Runs As Fast As MobileNet While Maintaining High Performance
Continue reading | Check out the paper, github
What are some alternatives?
semantic-segmentation-pytorch - Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset
PyTorch-Model-Compare - Compare neural networks by their feature similarity
PaddleViT - :robot: PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+
Efficient-AI-Backbones - Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
dytox - Dynamic Token Expansion with Continual Transformers, accepted at CVPR 2022
SINet - Camouflaged Object Detection, CVPR 2020 (Oral)
predictive-spy - Spying on Apple’s new predictive text model
dgcnn.pytorch - A PyTorch implementation of Dynamic Graph CNN for Learning on Point Clouds (DGCNN)
llama.cpp - LLM inference in C/C++
PixelLib - Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.