peft

We have hosted the application peft in order to run this application in our online workstations with Wine or directly.

Quick description about peft:

Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of pre-trained language models (PLMs) to various downstream applications without fine-tuning all the model's parameters. Fine-tuning large-scale PLMs is often prohibitively costly. In this regard, PEFT methods only fine-tune a small number of (extra) model parameters, thereby greatly decreasing the computational and storage costs. Recent State-of-the-Art PEFT techniques achieve performance comparable to that of full fine-tuning.

Features:

• Accelerate for large scale models leveraging DeepSpeed and Big Model Inference
• Get comparable performance to full finetuning by adapting LLMs to downstream tasks using consumer hardware
• GPU memory required for adapting LLMs on the few-shot dataset
• Parameter Efficient Tuning of Diffusion Models
• GPU memory required by different settings
• Parameter Efficient Tuning of LLMs for RLHF components such as Ranker and Policy

Programming Language: Python.
Categories: