huggingface/smol-course resource

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

6731 stars · 2276 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A free, open-source course from Hugging Face on aligning small language models (SmolLM3, SmolVLM2) to specific use cases, covering instruction tuning, evaluation, preference alignment like DPO, and vision-language models. It is designed to run on modest local hardware with minimal GPU requirements and includes exercises, a leaderboard, and community peer review.

Use cases

• learn how to fine-tune a small language model
• align an LLM to a custom domain with DPO
• run LLM fine-tuning on a local machine without paid GPUs
• evaluate fine-tuned language models with benchmarks
• adapt multimodal vision-language models
• generate synthetic training data for a custom domain

When to choose

• you want a hands-on, practical introduction to LLM alignment and fine-tuning
• you have limited compute and need everything to run locally
• you want to work with SmolLM3 or SmolVLM2 specifically
• you prefer community-reviewed, open course material

When to avoid

• you need production-scale training of large models on multi-GPU clusters
• you want a reference tool or library rather than educational material
• you need coverage of topics still marked unreleased, like reinforcement learning or synthetic data

Facets

learning-resource · maturity active

machine-learning llm-training rag prompt-engineering large-language-models machine-learning education tutorials python cross-platform fine-tuning alignment dpo instruction-tuning small-language-models vision-language-models hugging-face jupyter-notebooks course

Member repositories

For agents

markdown · JSON · MCP: product_card(name="huggingface/smol-course")