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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
Getting started with JAX (MLPs, CNNs & RNNs)
Learn the building blocks of JAX and use them to build some standard Deep Learning architectures (MLP, CNN, RNN, etc.).
jax xla autograd tpu
MedicalZoo PyTorch
A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation
medical-image-segmentation volumetric-segmentation medical-image-proccessing deep-learning
T5 fine-tuning
A colab notebook to showcase how to fine-tune T5 model on various NLP tasks (especially non text-2-text tasks with text-2-text approach)
natural-language-processing transformers text-2-text t5
Finetuning Transformers with JAX + Haiku
Walking through a port of the RoBERTa pre-trained model to JAX + Haiku, then fine-tuning the model to solve a downstream task.
jax haiku roberta transformers
Customizing What Happens in Fit()
How to leverage the convenient features of fit() with a custom training loop.
tensorflow keras training tutorial
FastHugs: Sequence Classification with Transformers and Fastai
Fine-tune a text classification model with HuggingFace 🤗 transformers and fastai-v2.
transformers fastai huggingface sequence-classification
Introduction to Differential Calculus
Introduces differential calculus: derivatives, partial derivatives and gradients.
differential-calculus math linear-algebra tutorial
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