Projects Tagged with Fine-Tuning: Model Optimization, Transfer Learning, LoRA & PEFT Implementations
Explore projects tagged "fine-tuning" to discover hands-on implementations of model optimization and transfer learning, including long-tail techniques like parameter-efficient fine-tuning (PEFT), LoRA, adapters, instruction tuning for LLMs, domain-adaptive fine-tuning, and hyperparameter search. This curated list of projects shows how teams and open-source contributors apply fine-tuning pipelines using Hugging Face, PyTorch, and TensorFlow, with reproducible training recipes, dataset preparation tips, evaluation metrics, and deployment strategies to reduce inference cost and improve task accuracy. Use the filtering UI to narrow results by framework, model family, dataset, or compute profile, then click into projects to access code, benchmarks, and deployment guides—start exploring and replicating fine-tuning workflows today.
