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Learn how to fine-tune Sequence-to-Sequence Large Language Models (LLMs) like T5 for summarization tasks in this 15-minute tutorial. Follow along with the latest HuggingFace code implementation to further fine-tune a pre-trained T5 model using a new training dataset, running the complete process on a free Google Colab notebook with Tesla T4 GPU support. Explore professional-grade model training techniques while working directly with the official HuggingFace transformers repository examples for PyTorch-based summarization tasks.
Syllabus
Fine-tune Seq2Seq LLM: T5 Professional | on free Colab NB
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