How Retrieval Augment Generation (RAG) makes LLMs smarter than before
By feeding LLMs the necessary domain knowledge, prompts can be given context and yield better results. RAG can decrease hallucination along with several other advantages.
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Kevin Vu
Quantization and LLMs – Condensing models to manageable sizes
The scale and complexity of LLMs The incredible abilities of LLMs are powered by their vast neural networks which are made up of billions of… Read More »Quantization and LLMs – Condensing models to manageable sizes
Diffusion and denoising – Explaining text-to-image generative AI
The concept of diffusion Denoising diffusion models are trained to pull patterns out of noise, to generate a desirable image. The training process involves showing… Read More »Diffusion and denoising – Explaining text-to-image generative AI
Question answering tutorial with Hugging Face BERT
What is Question Answering AI Question answering AI refers to systems and models designed to understand natural language questions posed by users and provide relevant… Read More »Question answering tutorial with Hugging Face BERT