Generate audiobooks from e-books, voice cloning & 1158+ languages!
这是一份入门AI/LLM大模型的逐步指南,包含教程和演示代码,带你从API走进本地大模型部署和微调,代码文件会提供Kaggle或Colab在线版本,即便没有显卡也可以进行学习。项目中还开设了一个小型的代码游乐场🎡,你可以尝试在里面实验一些有意思的AI脚本。同时,包含李宏毅 (HUNG-YI LEE)2024生成式人工智能导论课程的完整中文镜像作业。
A Python package for interactive geospatial analysis and visualization with Google Earth Engine.
Synapsa Commons: free, hands-on AI courses that run anywhere (Colab, Kaggle, Binder, Codespaces, Jupyter). EU AI Act conformity evidence, model validation, predictive maintenance, document extraction, retrieval and RAG, AI agents and MCP, a simulated humanoid. Every lesson autograded. From the team building Synapsa.
Isaac Lab API, powered by MuJoCo-Warp, for RL and robotics research
Python package for compiling and analyzing quantum algorithms to simulate electronic structures.
A CLI for interacting with Google Colab runtimes
A coding-free framework built on PyTorch for reproducible deep learning studies. PyTorch Ecosystem. 🏆26 knowledge distillation methods presented at TPAMI, CVPR, ICLR, ECCV, NeurIPS, ICCV, AAAI, etc are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark.
AgentQL is a suite of tools for connecting your AI to the web. Featuring a query language and Playwright integrations for interacting with elements and extracting data quickly, precisely, and at scale. Includes REST API, Python and JavaScript SDKs, browser debugger.
Making Protein Design accessible to all via Google Colab!
Swap a large text encoder for a small one with a learned linear projection. MiniMax H3 conditioning from 15.7 GB down to 5.2 GB.
Standalone Codex skill for MiniMax H3 Colab reference-to-video generation
A local app that rents a GPU in your own Colab account and serves Qwen3.8 on it: 27B on an A100-40G, or Flash-Next (125B-A6B MoE) on an A100-80G. The cost is shown before it starts; chat with images; Codex or any OpenAI client uses a fixed local /v1. Auto-stop, CU ledger, live prefill/decode. Windows, macOS, Linux.
Open reproduction of TypeSafe Jev: a 150M typed decision engine (noul/choice/score in one non-autoregressive pass, calibrated confidence). 0.697 vs Jev's 0.727, 2.5x better calibrated, 4x faster, free. Trains on a Colab T4 in 30 min.
Installable Codex skill for training MiniMax H3 Ref2VA LoRAs on Google Colab