Search
2 articles for “Low- Rank Adaptation”
-
A Reviewed Study On Cpu-Optimized Parameter-Efficient Fine- Tuning For Large Language Models To Increase Accuracy Using Lora
Abstract: The fast proliferation of Large Language Models (LLMs) has increased the need to optimize the process of fine-tuning but the existing workflows that require a GPU are still expensive, intensive, and unavailable to most researchers. This paper is driven by the desire to have a more cost-efficient and democratized version by examining a CPU-efficient implementation of Parameter-Efficient Fine-Tuning (PEFT) based on Low-Rank Adaptation (LoRA). The major purpose of the study …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
-
Adaptation of Finger Millet (Eleusine coracana) Varieties in Southern Ethiopia
Abstract: Finger millet (Eleusine coracana) is one of the cereal food and feed crops grown in Ethiopia. The crop is considered a low input crop. Unavailability of improved varieties was realized as one of the major production constraints at all potential areas in southern Ethiopia. The present study was conducted with an objective to identify the adaptive, preferred and better yielding finger millet varieties for further demonstration and pre-scale up. The …
Published in Research & Reviews : Journal of Botany · Vol. 14, Issue 2, 2025 · pp. 1–5 Read article