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Python - 100天从新手到大师
21 Lessons, Get Started Building with Generative AI
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Examples and guides for using the OpenAI API
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.
12 Lessons to Get Started Building AI Agents
12 Weeks, 24 Lessons, AI for All!
This is a repo with links to everything you'd ever want to learn about data engineering
🔊 Text-Prompted Generative Audio Model
Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. The next cohort starts in January 2026. Join the course here 👇🏼
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.
Anthropic's Interactive Prompt Engineering Tutorial
《开源大模型食用指南》针对中国宝宝量身打造的基于Linux环境快速微调（全参数/Lora）、部署国内外开源大模型（LLM）/多模态大模型（MLLM）教程
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
A guidance language for controlling large language models.
Official code repo for the O'Reilly Book - "Hands-On Large Language Models"
Neural Networks: Zero to Hero
Instruct-tune LLaMA on consumer hardware
Anthropic's educational courses
Qwen3-VL is the multimodal large language model series developed by Qwen team, Alibaba Cloud.
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
StableLM: Stability AI Language Models
A multi-voice TTS system trained with an emphasis on quality
Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
PyTorch code and models for the DINOv2 self-supervised learning method.
LAVIS - A One-stop Library for Language-Vision Intelligence
QLoRA: Efficient Finetuning of Quantized LLMs