Transformers

This blog post will show how easy it is to fine-tune pre-trained Transformer models for your dataset using the Hugging Face Optimum library on Graphcore Intelligence Processing Units (IPUs). Written by: Tim Santos, Eva Woodbridge (Graphcore), Julien Simon (Hugging Face) This blog post will show how easy it is to…

Translated by Hu Yanjun, Shen Jiali, Dong Wenwen, Jia Chuan Starting with BERT in 2018, large models sprung up one after another, including GPT-3 and ViT, whose parameters are counted in billions. Explosive growths in model size happen so frequently that they can hardly impress AI developers. …

由於複雜的注意力機制和模型設計，大多數現有的Vision Transformer模型無法像卷積神經網路(CNN)那樣高效的執行在現實的工業部屬場景中。 這也凸顯了一個問題，該如何在保有Vision Transformer性能的同時達到與CNN一樣快的推論速度? 近期的一些論文試圖設計CNN-Transformer的混和架構來解決上述問題，但整體的效能尚未能達到令人滿意的程度，因此字節跳動的研究者們提出了能有效部屬在現實工業場景中的Vision Transformer-Next-ViT (Next Generation Vision Transformer)，在準確率與速度都能兼顧情況下，與EfficientNet、PoolFormer等優秀的模型比較，有過之而無不及(如下圖)。 Next-ViT 架構 為了解決效率問題而提出的Next-ViT主要可由三個重要的部分組成: NCB — Next Convolution Block

Imbalance data problem is the most common scenario in real life. The predominant methods to handle such data are. Oversampling Undesampling Weighted loss to handle imbalance Oversampling This method duplicates the minority class in order to balance both classes. The drawback of this method is that it significantly increases the…

As traditional media struggles to come to terms with the digital age, the linguistic relationships revealed during NLP modelling offer a tantalising glimpse into a future where journalistic instinct and data combine to reveal previously hidden insights and help uphold reporting standards. We can analyse parameters and word vectors learned…

*** If you want to read my article in english, please visit Towards Data Science (DETR: End-to-End Object Detection with Transformers and Implementation of Python) Facebook’un research ekibi tarafından yayınlanan DETR makalesinde transformers yapılarını kullanarak obje tanıma işlemi gerçekleştirilmiştir. …

August 06, 2022 Machine-learning-powered code completion tools have slowly but surely started to make their way into software engineers’ everyday lives. Earlier versions of some of these tools have been around for years, however, the release of GitHub Copilot, which delivered quality multi-line suggestions raised the bar for what deep-learning-based…

For a presentation at DataHour, I needed to train a Vision Transformer model on images of Indian Food (more about the talk here). The overall approach is based on this blog post: Fine-Tune ViT for Image Classification with 🤗 Transformers I started with this dataset of Indian Foods. I then…

Introduction MHFormer: Multi-Hypothesis Transformer for 3D Human Pose Estimation(CVPR 2022) is a model Estimating 3D human poses from monocular videos. Multi-Hypothesis Transformer learns spatio-temporal representations of multiple plausible hypotheses and build strong relationships across them. …