Resources

• DeeBERT: Teaching BERT When to Stop Thinking

  Why does BERT need twelve layers to classify “I love this movie” as positive?

• Early Exiting: The Under-Hyped Compression Method

  Why are we burning GPU hours to answer “2 + 2 = 4”?

• Instruction Fine-Tuning Fundamentals

  Instruction Fine-Tuning (IFT) is the secret sauce that transforms generic language models into obedient AI assistants.

• Scaling Machine Learning Experiments With neptune.ai and Kubernetes

  Link post: managing and scaling experiment tracking with Neptune and Kubernetes.

• Case Study: MLOps for NLP-powered Media Intelligence using Metaflow

  Link post: case study on building NLP media intelligence with Metaflow.

• Scaling-up PyTorch inference: Serving billions of daily NLP inferences with ONNX Runtime

  Link post: engineering write-up on large-scale PyTorch inference with ONNX Runtime.

• Atlastic Reputation AI: Four Years of Advancing and Applying a SOTA NLP Classifier

  Link post: paper on advancing and applying a SOTA NLP classifier.