Explanation: Code models are specifically trained to understand and generate programming language code, which distinguishes them from general language models. Why Other Options are Incorrect:
model (the student), not the other way around. C. The goal is to improve the smaller model, not to enhance the teacher model. D. Knowledge distillation does not involve skipping layers; it’s about creating a more compact model with similar performance. Your company wants to create a research assistant chatbot using OCI Generative AI Service that can retrieve and generate answers to technical questions from a large corpus of internal documents. The chatbot should integrate Retrieval -Augmented Generation (RAG) to improve its accuracy and use LangChain for processing complex queries. Which components would be the most appropriate to achieve this?
Explanation: Transfer Learning involves adapting a pre -trained model to new tasks by updating its parameters. Incremental Learning involves continuously updating the model as new data arrives, allowing it to learn from new data without starting from scratch. Why Other Options are Incorrect:
Explanation: Provisioning a dedicated GPU cluster through OCI AI Services and using OCI Data Science for fine- tuning ensures access to the right resources and tools optimized for training large models. Why Other Options are Incorrect:
efficient handling of large -scale datasets and complex dependencies in text. Why Other Options are Incorrect: B. RNNs are not used in Transformer -based models; Transformers have largely replaced RNNs for these tasks. C. CNNs are primarily used for image processing and not for text -based models like GPT -3 and BERT. D. SVMs are not suitable for the scale and complexity of LLM training. You plan to use an AI cluster for a batch processing task that will take 5 hours per day over 6 days. How many unit hours are required in total?
➢ TOTAL QUESTIONS: 420 In LangChain, which retriever search type is used to balance between relevancy and diversity?
