Explore open-source MLM evolution: early models to powerful Transformers like GPT, BERT. Learn fine-tuning, dynamic padding, Hugging Face tools for BERT sequence classification. Enhance search engines, diverse tasks.
Trace open-source MLM evolution: early models ➔ potent Transformers (GPT, BARD). Diff auto-regressive/auto-encoding. Dive into fine-tuning, frozen layers for speed. Learn dynamic padding, Hugging Face tools for GPU. Step-by-step BERT seq. classification fine-tuning via Transformers for search enhancement, tasks. Demo optimizing, fine-tuning models: data load/tokenize/pad/train (dynamic, frozen layers, gradient acc.). QNLI dataset, balance accuracy/train time, data select, test sig. Goal: heightened task-specific model performance/efficiency
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