The badge earner understands the concepts of large language models (LLMs) for natural language processing (NLP) tasks. They know how to fine-tune models with PyTorch and Hugging Face using parameter-efficient fine-tuning (PEFT) methods like low-rank adaptation (LoRA) and quantized low-rank adaptation (QLoRA). They also understand model quantization and prompting and how to use pre-trained transformers for language tasks.

• Type Validation
• Level Intermediate
• Time Days
• Cost Paid