Fine-tuning is a powerful technique to adapt pre-trained models to specific tasks. Here's a quick guide:

  1. What is Fine-tuning?
    🧠 Fine-tuning involves retraining a model on a smaller, task-specific dataset to improve performance. It's commonly used in NLP for tasks like text classification, named entity recognition, etc.

  2. Steps to Fine-tune

    • Prepare your dataset
    • Load a pre-trained model
    • Configure training parameters
    • Train the model
    • Evaluate and deploy
  3. Resources

Fine_tuning_Process

For visualizing model architectures, check out:
Model Visualization Tools

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HF Overview