100+ Free LMP-C01 Practice Questions

LLM Fundamentals and Alibaba Cloud Integration

Understand transformer architecture and self-attention, tokenization and context windows, and inference parameters such as temperature, top_p, presence_penalty, and seed. Select among Qwen variants (qwen-turbo, qwen-plus, qwen-max, qwen-long, qwen-vl) and access them through DashScope and Model Studio (Bailian), including the OpenAI-compatible interface and function calling.

Retrieval-Augmented Generation (RAG)

Generate embeddings, store them in a vector database, and use semantic, hybrid, and re-ranked retrieval. Chunk documents with overlap, apply similarity thresholds, build Model Studio knowledge bases, and ground answers in retrieved context to reduce hallucination, with incremental ingestion for freshness.

Fine-Tuning Techniques

Apply supervised fine-tuning with high-quality instruction-output pairs, parameter-efficient methods like LoRA, and full-parameter fine-tuning when warranted. Tune hyperparameters such as learning rate, avoid overfitting with held-out data, and use PAI components including PAI-DSW notebooks and PAI-DLC distributed training.

Model Evaluation and Optimization

Measure quality with BLEU, ROUGE, perplexity, and F1, evaluate RAG faithfulness and recall, and apply LLM-as-a-judge and human evaluation. Run benchmark and regression tests, A/B test prompts and models, and monitor for data and model drift over time.

LLM Deployment on Alibaba Cloud

Serve models with PAI-EAS using autoscaling and load balancing, apply quantization for efficient inference, and control cost with caching, max_tokens limits, and model routing. Secure API keys, enforce rate limits at a gateway, monitor latency, errors, and token usage, and release with canary rollouts.

Ethics, Compliance, and Advanced Topics

Evaluate and mitigate bias, protect privacy by minimizing and redacting PII, and add guardrails and content moderation. Defend against prompt injection with least-privilege tools, align behavior with RLHF, keep humans in the loop for high-stakes decisions, respect data residency, red-team before release, and disclose AI-generated content.