Projects Tagged with finetuning: Model Fine-Tuning, Transfer Learning, and PEFT Implementations
Explore projects tagged finetuning to find repositories, experiments, and production pipelines that apply model fine-tuning, transfer learning, instruction tuning, and parameter-efficient techniques (LoRA, adapters, PEFT) for domain adaptation and improved performance. This filtered list of projects (nav: projects; pillar: tags) provides actionable insights — filter by framework (PyTorch, TensorFlow), dataset size, checkpoint type, and hyperparameters; compare few-shot, low-shot and full fine-tuning trade-offs; and adopt best practices for learning-rate schedules, mixed precision, regularization, and evaluation metrics. Browse the results to clone code, reproduce benchmarks, select high-impact implementations for integration, or contribute improvements — start exploring projects tagged finetuning now.
