QLoRA
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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
PEFT (Parameter-Efficient Fine-Tuning) is a broader category of methods that includes QLoRA. QLoRA is one specific PEFT technique.
LoRa
LoRA (Low-Rank Adaptation) is a PEFT technique similar to QLoRA. QLoRA builds upon LoRA to improve memory efficiency.
Llama
QLoRA is often used to fine-tune Llama models.
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Which job functions commonly mention QLoRA?
Prompt Engineer
0.2% of all Prompt Engineer jobs mention QLoRA
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jobs on Sumble
AI Engineer
0.1% of all AI Engineer jobs mention QLoRA
View 108
jobs on Sumble
Machine Learning
0.1% of all Machine Learning jobs mention QLoRA
View 61
jobs on Sumble
Data Scientist
68 Data Scientist jobs mention QLoRA
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jobs on Sumble
Applied Scientist
3 Applied Scientist jobs mention QLoRA
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jobs on Sumble
Which organizations are mentioning QLoRA?
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