OpenDelta is an open-source parameter-efficient fine-tuning library that enables efficient adaptation of large-scale pre-trained models using delta tuning techniques. OpenDelta is a toolkit for parameter-efficient tuning methods (we dub it as delta tuning), by which users could flexibly assign (or add) a small amount parameters to update while keeping the most parameters frozen. By using OpenDelta, users could easily implement prefix-tuning, adapters, Lora, or any other types of delta tuning with preferred PTMs.
Features
- Supports parameter-efficient tuning for transformer models
- Works with popular models like BERT, GPT, and T5
- Open-source with flexible customization for NLP tasks
- Compatible with Hugging Face Transformers and PyTorch
- Reduces computational cost and memory footprint for fine-tuning
- Implements multiple tuning strategies including adapter layers
Categories
Natural Language Processing (NLP)License
Apache License V2.0Follow OpenDelta
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