anthropics / prompt-eng-interactive-tutorial
Anthropic's Interactive Prompt Engineering Tutorial
See what the GitHub community is most excited about today.
Anthropic's Interactive Prompt Engineering Tutorial
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
This repository delivers end-to-end, code-first tutorials covering every layer of production-grade GenAI agents, guiding you from spark to scale with proven patterns and reusable blueprints for real-world launches.
Polymarket Data Retriever that fetches, processes, and structures Polymarket data including markets, order events and trades.
A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.
Finviz analysis python library.
Qwen3-VL is the multimodal large language model series developed by Qwen team, Alibaba Cloud.
Common recipes to run vLLM
本项目是一个面向小白开发者的大模型应用开发教程,在线阅读地址:https://datawhalechina.github.io/llm-universe/
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable music generation LM with textual and melodic conditioning.
Reference PyTorch implementation and models for DINOv3
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.
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.
Examples and guides for using the OpenAI API
📚 从零开始的大语言模型原理与实践教程