Explore how to leverage Hugging Face's "accelerate" library for efficient PyTorch NLP model training and fine-tuning on Colab TPU and multi-GPU setups. Learn to adapt existing PyTorch training scripts for multi-GPU/TPU environments with minimal code changes. Discover the notebook_launcher function for distributed training in Colab or Kaggle notebooks with TPU backends. Gain hands-on experience using Google Colab to implement these techniques, enhancing your ability to scale NLP model training across multiple GPUs or TPUs.
PyTorch NLP Model Training and Fine-Tuning on Colab TPU Multi-GPU with Accelerate
1littlecoder via YouTube
Overview
Syllabus
Pytorch NLP Model Training & Fine-Tuning on Colab TPU Multi GPU with Accelerate
Taught by
1littlecoder
Related Courses
-
Create a Large Language Model from Scratch with Python – Tutorial
-
Fine-tuning Flan-T5 LLM with HuggingFace Accelerate - Tutorial
-
Multi-GPU Fine-tuning with DDP and FSDP
-
Optimizing LLM Fine-Tuning with PEFT and LoRA Adapter-Tuning for GPU Performance
-
Intro to Hugging Face - Fine-Tuning BERT for NLP Tasks
-
Fine-tuning Vision Language Models with PaLiGemma-3B - A Practical Guide
