GPU vs TPU for LLM Training: A Comprehensive Analysis
Explore the critical differences in GPU vs TPU for LLM Training to optimize performance, memory, and cost-efficiency.
What are Pre-Trained Multi-Task Generative AI Models?
Discover how pre-trained multi-task generative AI models transform various tasks like text generation, coding, and content creation.
Multi-task Fine-Tuning of LLMs (Large Language Models)
Explore the benefits, methodology, and real-world applications of multi-task fine-tuning for enhancing LLMs (large language models)
Instruction Tuning Vs Fine-Tuning of LLMs
A comprehensive review of Instruction Tuning Vs Fine-Tuning in large language models for optimal performance.
Supervised Fine-Tuning Vs RLHF for LLMs
Comparing Supervised Fine-Tuning vs. RLHF: Tailoring language models for tasks—data efficiency, flexibility, human alignment, challenges.
Reinforcement Learning from Human Feedback (RLHF) for LLMs
RLHF shapes LLMs through human feedback, reducing bias. Embracing responsible AI evolution and impactful collaborations.
Soft Prompting for Fine-Tuning of Large Language Models
Soft prompting: Tailoring large language models efficiently with subtle cues for adaptive, task-specific enhancements.
LoRA vs. Fine-Tuning: Optimizing LLM Adaptation
LoRA achieves efficiency without compromising model quality, outperforming full fine-tuning in various benchmarks.