AI Model2024
Performs document OCR, layout analysis, reading-order detection and table recognition across 90+ languages using a ~650M-parameter vision–language model; offers per-page and per-block modes and supports GPU (vllm) and CPU/Apple Silicon backends.
AI Audio2024
Clones a voice from a 5-second sample for zero-shot TTS, or fine-tunes on ~1 minute of audio for few-shot synthesis. Covers Chinese, English, Japanese, Korean, and Cantonese, with a WebUI bundling vocal separation, ASR, and dataset labeling.
AI Image2024
Reworks AUTOMATIC1111's Stable Diffusion WebUI onto a custom backend that auto-manages GPU memory to speed inference and cut VRAM use. Adds native FLUX support with NF4/GGUF quantization and a UNetPatcher framework for model-agnostic extensions.
AI Audio2024
Converts e-books (epub, pdf, mobi, docx, and more) into chapter-aware audiobooks, with optional zero-shot voice cloning. Bundles eight TTS engines including XTTSv2 and Bark, and covers 1,158 languages via Meta's MMS — all runnable on CPU or GPU.
Embodied AI2024
A PyTorch-native, hardware-agnostic stack for robot learning: data collection, training, and deployment across 11+ robots, from SO100 to Unitree G1. Includes imitation, RL, and vision-language-action policies (ACT, Diffusion, Pi0, SmolVLA).
AI Model2024
Pocket-sized multimodal LLM for efficient image- and video-understanding on mobile and edge devices, featuring mixed 4x/16x visual-token compression (MiniCPM‑V 4.6), compact 1.3B variants, and ready guides for iOS/Android/HarmonyOS deployment.
AI Train2024
Runs GPT-4o-class vision, speech, and full-duplex audio-video conversation on a 9B model small enough to deploy on phones and tablets. The 4.5 release scores 77.6 on OpenCompass and adds real-time bilingual voice with voice cloning.
AI Deploy2024
GPU kernel library for LLM inference attention, sampling, and KV-cache, built on block-sparse formats with JIT-compiled customizable templates. Reports 29-69% inter-token-latency cuts vs compiler backends; powers SGLang, vLLM, and MLC-Engine.
AI Video2024
Generates short videos from text, images, or videos and ships a full training/inference pipeline with checkpoints and demos. Key features include multi-stage training (VAE / 3D-VAE), rectified-flow training, video compression modules, and support for 2s–16s clips at up to 720p. Best for researchers and engineers who can provide substantial GPU resources.
AI Train2024
End-to-end framework for running and reproducing foundation-model research workflows — from data curation and tokenization to training and evaluation. Emphasizes reproducibility by recording every step (including failed runs) and expressing experiments as dependency-ordered steps.
Hands-on coding tutorial series for large language models with slides and runnable notebooks covering fine-tuning, prompting, RLHF, safety, steganography, watermarking, multimodal models, GUI agents, and deployment. Community-maintained, free course materials for students and researchers.
AI Train2024
Accelerates video generation with a unified framework for inference, finetuning, LoRA, distillation, sparse attention, and distributed execution for research and demos.