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 Hours
• Cost Paid