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Top Down Introduction to BERT with HuggingFace and PyTorch
I will also provide some intuition into how BERT works with a top down approach (applications to algorithm).
bert top-down huggingface pytorch
DETR: End-to-End Object Detection with Transformers
A new method that views object detection as a direct set prediction problem.
object-detection image-segmentation panoptic-segmentation transformers
VirTex: Learning Visual Representations from Textual Annotations
We train CNN+Transformer from scratch from COCO, transfer the CNN to 6 downstream vision tasks, and exceed ImageNet features despite using 10x fewer ...
convolutional-neural-networks transformers coco visual-representations
Paraphrase Any Question with T5 (Text-To-Text Transformer)
Given a question, generate paraphrased versions of the question with T5 transformer. Pretrained model and training script provided.
t5 transformers huggingface pytorch
How to Train Your Neural Net
Deep learning for various tasks in the domains of Computer Vision, Natural Language Processing, Time Series Forecasting using PyTorch 1.0+.
pytorch python deep-learning computer-vision
Summary of 🤗 Transformers Models
A high-level summary of the differences between each model in HuggingFace's Transformer library.
transformers huggingface summary natural-language-processing
The Transformer … “Explained”?
An intuitive explanation of the Transformer by motivating it through the lens of CNNs, RNNs, etc.
transformers natural-language-processing tutorial article
Generate Boolean (Yes/No) Questions From Any Content
Question generation algorithm trained on the BoolQ dataset using T5 text-to-text transformer model.
question-generation transformers huggingface t5
Self Supervised Representation Learning in NLP
An overview of self-supervised pretext tasks in Natural Language Processing
self-supervised-learning natural-language-processing tutorial article
Zero-Shot Learning for Text Classification
A visual summary of “Train Once, Test Anywhere” paper for zero-shot text classification
zero-shot-learning natural-language-processing tutorial article
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