Search Results for author:
Found 2 papers, 1 papers with code
DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines
We integrate our constructs into the recent DSPy programming model for LMs, and present new strategies that allow DSPy to compile programs with LM Assertions into more reliable and accurate systems.
SlimFit: Memory-Efficient Fine-Tuning of Transformer-based Models Using Training Dynamics
This allows SlimFit to freeze up to 95% of layers and reduce the overall on-device GPU memory usage of transformer-based models such as ViT and BERT by an average of 2. 2x, across different NLP and CV benchmarks/datasets such as GLUE, SQuAD 2. 0, CIFAR-10, CIFAR-100 and ImageNet with an average degradation of 0. 2% in accuracy.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
