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Day 51: Containerization of LLM Applications

Day 50: Building a REST API for LLM Inference

Day 45: Interpretability Techniques for LLMs

Day 44: Probing Tasks for LLMs

Day 42: Continual Learning in LLMs

Day 41: Multilingual LLMs

Day 38: Question Answering with LLMs

Day 40: Constrained Decoding with LLMs

Day 48: Quantization of LLMs

Day 35 - BERT: Bidirectional Encoder Representations from Transformers

Day 34 - XLNet: Generalized Autoregressive Pretraining for Language Understanding

Day 33 - ALBERT (A Lite BERT): Efficient Language Model

Day 32 - Switch Transformers: Efficient Large-Scale Models

Day 31: Longformer - Efficient Attention Mechanism for Long Documents

Day 52: Monitoring LLM Performance in Production

Day:30 Reformer: Efficient Transformer for Large Scale Models

Day 29: Sparse Transformers: Efficient Scaling for Large Language Models

Day 49: Serving LLMs with ONNX Runtime

Day 27: Regularization Techniques for Large Language Models (LLMs)

Day 26: Learning Rate Schedules

Day 47: Model Compression for Deployment

Day 46: Adversarial Attacks on LLMs

Mixed Precision Training

Day 22: Distributed Training in Large Language Models

Day 43: Evaluation Metrics for LLMs

Ethical Considerations in LLM Development and Deployment

Day 36: Text Classification with LLMs

Day 39: Summarization with LLMs

Day 37: Named Entity Recognition (NER) with LLMs

Day 28: Model Compression Techniques for Large Language Models (LLMs)