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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 panoptic-segmentation transformers computer-vision
Model Serving using FastAPI and Streamlit
Simple example of usage of streamlit and FastAPI for ML model serving.
fastapi streamlit deeplabv3 semantic-segmentation
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
A Python framework for Automated Machine Learning (AutoML), hyperparameter tunning and program synthesis in general.
automl python machine-learning code
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
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
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