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Unleashing the Power of `collate_fn`: Streamlining Data Preparation for PyTorch and Transformers
Dataloaders: In PyTorch, DataLoader efficiently iterates over your dataset in batches. It takes a dataset and various parameters like batch size
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Saving Time, Saving Models: Efficient Techniques for Fine-Tuned Transformer Persistence
Import Necessary Libraries: import transformers from transformers import TrainerImport Necessary Libraries:Create a Trainer Instance (Optional):
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Disabling the "TOKENIZERS_PARALLELISM=(true | false)" Warning in Hugging Face Transformers (Python, PyTorch)
When you use the tokenizer from Hugging Face Transformers in conjunction with libraries like multiprocessing for parallel processing