Exam AWS Certified AI Practitioner AIF-C01 topic 1 question 97 discussion

In Stable Diffusion, Classifier-Free Guidance (CFG) scale controls how strongly the model follows the text prompt versus generating freely (more randomness). A higher CFG scale means the model adheres more closely to the prompt, resulting in more specific and detailed images. A lower CFG scale introduces more randomness, leading to less relevant or vague outputs.

The best solution to increase the specificity of generated images in a Retrieval Augmented Generation (RAG) system using Amazon Bedrock and Stable Diffusion is C. Increase the classifier-free guidance (CFG) scale. Explanation: Classifier-Free Guidance (CFG) Scale: This parameter directly controls how closely the generated image aligns with the text prompt. A higher CFG scale forces the model to pay more attention to the details in the prompt, resulting in images that are more specific and less random.

Explicação: A força do prompt (prompt strength) se refere ao grau de influência que o texto fornecido tem sobre a imagem gerada. Quando a força do prompt é baixa, o modelo (como o Stable Diffusion) pode gerar imagens mais abstratas ou genéricas. Ao aumentar a força do prompt, você orienta o modelo a seguir mais fielmente os detalhes fornecidos no texto, gerando imagens mais específicas e controladas — o que é justamente o que a empresa deseja.

In Retrieval Augmented Generation (RAG) with Stable Diffusion, the prompt strength determines how closely the generated image aligns with the given text description. By increasing prompt strength, the model places more emphasis on the input prompt, making the output more specific and detailed, which directly addresses the company's concern about random and lacking specific details in generated images.

Classifier-Free Guidance (CFG) is a technique used in generative models, especially in image generation tasks, that helps guide the generation process toward more specific or desired outputs. By increasing the CFG scale, the model's generated image becomes more closely aligned with the given text prompt, improving the specificity and control over the details in the generated image. A higher CFG scale ensures that the model generates images that are more faithful to the prompt by reducing randomness and making the generation more deterministic. This technique allows for more control over the image generation process, making it suitable for use cases like generating product images from text descriptions, where specific details are important.

The correct answer is C. Higher CFG scale makes generated images follow prompts more closely.

Increasing the classifier-free guidance (CFG) scale (Option C) will make the model pay more attention to the input text description, improving the specificity and detail of the generated images. This is the most effective method to increase the specificity of images in a Retrieval Augmented Generation (RAG) setup with Stable Diffusion.

Classifier-Free Guidance (CFG) is a technique used in diffusion models, such as Stable Diffusion, to guide the model toward generating outputs that closely align with the text prompt. By increasing the CFG scale, the model puts more emphasis on the textual prompt, leading to outputs that are more specific and less random. In this case, where the generated images lack specific details, increasing the CFG scale helps ensure the generated product images are more aligned with the input text descriptions.