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Learn the basics of Hugging Face Transformers library, including installation, pre-defined pipelines, and implementing models in PyTorch. Explore tokenization, attention masks, and model outputs in this practical coding guide.
Learn to build a CNN image classifier using PyTorch and CIFAR10 dataset. Covers data loading, model architecture, training, and validation, with practical coding examples for computer vision enthusiasts.
Explore convolutional kernels in CNNs, from basic concepts to practical applications in PyTorch. Learn visualization techniques and understand their impact on computer vision tasks.
Practical guide to image classification using CIFAR10 dataset. Learn to load data, create DataLoaders, transform images, and visualize the dataset in PyTorch for computer vision tasks.
Practical guide to retraining BERT for masked language modeling using Hugging Face Trainer on the Microsoft Research Sentence Completion Challenge, with step-by-step Python implementation and performance evaluation.
Practical guide to applying Hugging Face language models for sentence completion, covering masked language modeling, data inspection, model application, and performance evaluation.
Learn to finetune RoBERTa for multi-label classification of unhealthy comments using PyTorch Lightning. Practical coding guide covers data preparation, model creation, training, and evaluation.
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