Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning
Paper
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2303.10512
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Published
PEFT papers
A collection of methods that have been implemented in the 🤗 PEFT library
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Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning
Paper • 2205.05638 • Published • 3 -
LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention
Paper • 2303.16199 • Published • 4 -
FedPara: Low-Rank Hadamard Product for Communication-Efficient Federated Learning
Paper • 2108.06098 • Published • 2 -
Navigating Text-To-Image Customization:From LyCORIS Fine-Tuning to Model Evaluation
Paper • 2309.14859 • Published • 4 -
Low-rank Adaptation of Large Language Model Rescoring for Parameter-Efficient Speech Recognition
Paper • 2309.15223 • Published • 19 -
Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning
Paper • 2303.02861 • Published • 2 -
Controlling Text-to-Image Diffusion by Orthogonal Finetuning
Paper • 2306.07280 • Published • 20 -
GPT Understands, Too
Paper • 2103.10385 • Published • 8 -
Prefix-Tuning: Optimizing Continuous Prompts for Generation
Paper • 2101.00190 • Published • 6 -
The Power of Scale for Parameter-Efficient Prompt Tuning
Paper • 2104.08691 • Published • 9 -
Combining Modular Skills in Multitask Learning
Paper • 2202.13914 • Published • 4