huggingface transformers

[1/1]

  1. 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
  2. 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):
  3. 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