colab

Unsloth Notebooks is a collection of 250+ open-source fine-tuning and reinforcement-learning notebooks for text, vision, audio, embeddings, and speech models, providing ready-to-use Colab notebooks with data preparation, training, and inference steps.

Recommended a GitHub repo for building a GPT-style Transformer from scratch without advanced libraries. With 13M parameters, it can be trained in one day on free Colab to generate grammatically correct text.

EveryonesLLM is an open-source Google Colab-based tutorial repository for building a nanoGPT-style LLM from scratch, with step-by-step chapters covering dataloading, embeddings, attention, training, and instruction tuning.

EveryonesLLM is an open-source tutorial that provides 29 chapters of Colab notebooks. It teaches users step by step to build a complete large language model from scratch on Google Colab, including pre-training and instruction fine-tuning, and supports Chinese.

The user excitedly notes that Google Colab is back, likely referring to a recent update or improvement.

Recommend an open-source free tutorial 'Hands-On Large Models', covering 12 chapters including language model basics, prompt engineering, semantic search, model fine-tuning, multimodal applications, etc. All code can be run directly in Colab.

A user demonstrates using OpenAI's Codex to automatically generate a Colab notebook that trains a ~10 million parameter transformer in JAX/Flax/Optax on addition, achieving high accuracy after 4000 steps on a T4 GPU.

The tweet announces that users can now fine-tune Google's Gemma 4 model for free in the browser using the Unsloth Colab notebook, significantly lowering the barrier to entry for model customization.