The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Python Data Science Handbook: full text in Jupyter Notebooks

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

A programming framework for agentic AI. Discord: https://aka.ms/autogen-dc. Roadmap: https://aka.ms/autogen-roadmap

Free Data Engineering course!

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

Implementing a ChatGPT-like LLM in PyTorch from scratch, step by step

The fastai book, published as Jupyter Notebooks

A guidance language for controlling large language models.

Kolmogorov Arnold Networks

A multi-voice TTS system trained with an emphasis on quality

Scripts for fine-tuning Meta Llama3 with composable FSDP & PEFT methods to cover single/multi-node GPUs. Supports default & custom datasets for applications such as summarization and Q&A. Supportin…

Zero-Shot Speech Editing and Text-to-Speech in the Wild

Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models l…

tiny vision language model

Examples and guides for using the Gemini API.

Materials for the Hugging Face Diffusion Models Course

Official Repository for "Eureka: Human-Level Reward Design via Coding Large Language Models" (ICLR 2024)

Automatic Generation of Visualizations and Infographics using Large Language Models

A powerful data & AI notebook templates catalog: prompts, plugins, models, workflow automation, analytics, code snippets - following the IMO framework to be searchable and reusable in any context.

A clear, concise, simple yet powerful and efficient API for deep learning.

LLM Finetuning with peft

Collection of notebook guides created by the Brev.dev team!

Training LLMs with QLoRA + FSDP

Doing simple retrieval from LLM models at various context lengths to measure accuracy

Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

ktrain is a Python library that makes deep learning and AI more accessible and easier to apply