A guide to transforming pretrained LLMs into text classifiers, with insights from the author's new book on building LLMs from scratch.
A tutorial on fine-tuning a BERT model for text classification using AWS Trainium instances and Hugging Face Transformers.
Explains four methods for detecting AI-generated text, including OpenAI's AI Classifier, DetectGPT, GPTZero, and watermarking, and how they work.
Learn how SetFit, a new approach from Intel Labs and Hugging Face, outperforms GPT-3 for text classification with minimal labeled data.
Learn how to fine-tune the XLM-RoBERTa model for multilingual text classification using Hugging Face libraries on cost-efficient Habana Gaudi AWS instances.
A tutorial on using task-specific knowledge distillation to compress a BERT model for text classification with Transformers and Amazon SageMaker.
A tutorial on building a non-English text classification model using BERT and Simple Transformers, demonstrated with German tweets.
Explains K-Fold cross-validation for ML models with a practical example using BERT for text classification.
A tutorial on text data classification using the BBC news dataset and PHP-ML for machine learning, covering data loading and preprocessing.
A developer shares their experience building a machine learning model to classify song moods (happy/sad) based on lyrics using Python and NLP.
Explores Naive Bayes classifiers for text classification, covering theory and applications like spam filtering and song lyric analysis.
An introduction to Naive Bayes classifiers, focusing on their theory and application in text classification tasks like spam filtering.
