Hugging Face
Hugging Face smol-course: LLM Fine-Tuning
Explore Hugging Face’s free smol-course for LLM instruction tuning and practical adaptation, with Python, GPU, evaluation, and certificate notes.
Intermediate10+ hoursCertificate
LLM Fine-Tuning courses and tutorials
Explore LLM fine-tuning learning for instruction data, adaptation, and evaluation, with Python prerequisites, compute notes, and a free Hugging Face route.
1 learning resource in this collection
About LLM Fine-Tuning
Fine-tuning changes a model using additional training examples. It can adapt behavior or a task format, but it is not automatically the best way to supply changing facts. Compare it with prompting and retrieval before investing in training.
Choose a useful starting point
Hugging Face's smol-course provides a focused free route with practical assignments. Python, machine-learning fundamentals, and familiarity with transformers help. Check accelerator needs, model licenses, and the quality of your training examples; free lessons do not imply unlimited free compute.
Build on the lessons
Prepare a small documented dataset and reserve examples for evaluation before training. Compare the adapted model with the original on the same tasks. Record configuration, compute use, and regressions as carefully as improvements.