Tech Insights

QLoRA

Last updated , generated by Sumble
Explore more →

What is QLoRA?

QLoRA (Quantization-aware Low-Rank Adaptation) is an efficient fine-tuning approach that reduces memory usage by quantizing a pre-trained language model to 4-bit precision and then fine-tuning only a small number of Low-Rank Adapters (LoRA). This allows large language models to be fine-tuned on a single GPU.

What other technologies are related to QLoRA?

QLoRA Complementary Technologies

PEFT (Parameter-Efficient Fine-Tuning) is a broader category of methods that includes QLoRA. QLoRA is one specific PEFT technique.
mentioned alongside QLoRA in 14% (76) of relevant job posts
LoRA (Low-Rank Adaptation) is a PEFT technique similar to QLoRA. QLoRA builds upon LoRA to improve memory efficiency.
mentioned alongside QLoRA in 4% (232) of relevant job posts
QLoRA is often used to fine-tune Llama models.
mentioned alongside QLoRA in 1% (71) of relevant job posts

Which organizations are mentioning QLoRA?

Organization
Industry
Matching Teams
Matching People

This tech insight summary was produced by Sumble. We provide rich account intelligence data.

On our web app, we make a lot of our data available for browsing at no cost.

We have two paid products, Sumble Signals and Sumble Enrich, that integrate with your internal sales systems.