AI learning guide

Best AI resources for open-source AI

Learn open models, Hugging Face tools, local inference, and deployment.

Best open-model course: Hugging Face LLM Course. Free Hugging Face course on transformers, LLMs, and inference. Start here if you want open-source AI foundations rather than hosted API habits only.

Best practical Llama recipes: Llama Cookbook. Meta Llama recipes for inference, RAG, fine-tuning, and applications. Use it when you want implementation examples around open Llama models.

Best model discovery hub: Hugging Face model hub. Catalog of open model checkpoints, datasets, demos, and metadata. Use it to compare what is actually available to run or fine-tune.

Open-source AI is more than model downloads

Open-source AI work includes model discovery, licenses, inference, fine-tuning, evaluation, hosting, quantization, and deployment. A model checkpoint is only the beginning.

Hugging Face's LLM Course and model hub are the natural starting points. Llama Cookbook helps with practical recipes once you choose a family. Official provider docs matter because model access and recommended deployment paths change.

Choose open models for a reason

Open models can be useful for privacy, customization, cost control, local inference, and research. They can also be harder to operate than hosted APIs. Learn the tradeoffs before committing.

A strong resource should help you compare quality, latency, hardware needs, context length, license terms, and deployment route on the workload you actually care about.

Recommended courses and resources

  1. The Illustrated Transformer

    Visual guide · Jay Alammar · Beginner to intermediate

    Transformer architecture still feels fuzzy.

  2. Hugging Face Skills

    Open-source skills and tutorial · Hugging Face · Intermediate to advanced

    You want reusable, open-source agent skills for training, fine-tuning, evaluating, quantizing, and publishing models with Codex, Claude Code, Gemini CLI, or another skills-compatible coding agent.

  3. Multi-Vector Embedding Models with Sentence Transformers

    Practical guide · Hugging Face · Intermediate to advanced

    You want a runnable guide to ColBERT-style late-interaction retrieval, including MaxSim scoring, retrieve-and-rerank, indexing, visual document retrieval, evaluation, and the storage-quality tradeoff versus dense embeddings.

  4. Training and Finetuning Multi-Vector Embedding Models with Sentence Transformers

    Training guide · Hugging Face · Advanced

    You need an end-to-end August 26, 2026 recipe for adapting a late-interaction retriever to your own domain, from datasets and losses through training, evaluation, and index optimization.

  5. OpenAI evals quickstart and datasets

    Guide · OpenAI · Intermediate

    You want OpenAI's current quickstart for turning examples into dataset-backed evals and improvement loops instead of relying on a deprecated docs path.

Roll a learning mission

Pick one small move from this guide instead of opening ten tabs.

Open mission

About this guide

Author: Learnetto Editorial Team. Learnetto maintains this AI learning directory by organizing public course pages, official documentation, educator material, and practical learning resources.

How it is made: Learnetto uses public course pages, official documentation, educator material, and directory data to compile these recommendations. AI may help draft and organize the page, but recommendations are checked against the listed sources, page topic, and learner intent.

Review policy: We only add a named personal reviewer when that person has substantially reviewed the page. Until then, the page is attributed to Learnetto rather than a founder, editor, or individual expert.

Last updated: September 18, 2026. Suggest a correction if a course, doc, or recommendation is outdated.

Videos to watch

Hugging Face agents course video thumbnail ►

Hugging Face agents course

Hugging Face

The last six months in LLMs in five minutes video thumbnail ►

The last six months in LLMs in five minutes

Simon Willison

Educators and sources

Educator / source Best for Skills Start with
Simon Willison profile photo
Developers, technical generalists LLM tools, Prompting, AI safety, Local models, Model selection Read the recent model-roundup posts, then try the llm command-line tool with two or three different providers.
Jay Alammar profile photo
Visual learners, developers Transformers, Embeddings, LLM concepts Read The Illustrated Transformer, then The Illustrated GPT-2.
Cohere For AI profile photo
Researchers, advanced builders NLP research, Open models, Multilingual AI Browse research posts and community programs.
Nils Reimers profile photo
Developers using embeddings Embeddings, Semantic search, Vector search, NLP Use the semantic textual similarity and semantic search examples.
Phil Schmid profile photo
Developers fine-tuning and deploying models Open models, Fine-tuning, Deployment, Transformers Pick one fine-tuning or inference guide and reproduce it end to end.
Lewis Tunstall profile photo
Developers learning Transformer applications Transformers, NLP, Open models, Fine-tuning Use the book notebooks alongside the Hugging Face course.

Resources

Hugging Face Skills

Open-source skills and tutorial · Hugging Face · Intermediate to advanced

You want reusable, open-source agent skills for training, fine-tuning, evaluating, quantizing, and publishing models with Codex, Claude Code, Gemini CLI, or another skills-compatible coding agent.

Multi-Vector Embedding Models with Sentence Transformers

Practical guide · Hugging Face · Intermediate to advanced

You want a runnable guide to ColBERT-style late-interaction retrieval, including MaxSim scoring, retrieve-and-rerank, indexing, visual document retrieval, evaluation, and the storage-quality tradeoff versus dense embeddings.

OpenAI evals quickstart and datasets

Guide · OpenAI · Intermediate

You want OpenAI's current quickstart for turning examples into dataset-backed evals and improvement loops instead of relying on a deprecated docs path.

OpenAI external models

Guide · OpenAI · Intermediate

You want to learn how OpenAI handles access to non-OpenAI model families before designing a mixed-provider or routed workflow.

OpenAI model optimization

Guide · OpenAI · Intermediate

You need a practical optimization loop across prompt changes, evals, and fine-tuning rather than guessing which knob to turn next.

Llama 4 prompt formats

Model docs · Meta Llama · Beginner to advanced

You need the current official Llama 4 prompt formats and model-card details before choosing Maverick or Scout for hosted or local deployment.

Mistral models overview

Model docs · Mistral AI · Beginner to advanced

You need to compare current Mistral families such as Devstral, Magistral, Voxtral, OCR, and general-purpose models.

Qwen API platform

API docs · Qwen · Beginner to advanced

You need official Qwen model-family context, deployment docs, and quickstarts before choosing a hosted or local workflow.

Together AI model catalog

Model catalog · Together AI · Beginner to advanced

You need to browse hosted open and proprietary models by provider and capability.

Together AI serverless models

Model docs · Together AI · Intermediate

You need to learn how serverless hosted model inference works before deploying an app.

Llama Cookbook

GitHub repo · Meta Llama · Beginner to advanced

You want Meta's practical recipes for inference, fine-tuning, RAG, and end-to-end Llama applications.

Llama API models

Model docs · Meta Llama · Beginner to advanced

You need Meta's current model-card and prompt-format index before choosing which Llama family, size, or integration path to test.

Mistral model selection guide

Guide · Mistral AI · Beginner to advanced

You want Mistral's official comparison of model families, pricing, context, and licensing before implementation.

Qwen quickstart

Quickstart · Qwen · Beginner to intermediate

You want the fastest official route into running Qwen3 with Hugging Face, vLLM, or SGLang.