AI Image2022
Browser-based control panel for running Stable Diffusion locally, built on Gradio. Bundles txt2img, img2img, inpainting, outpainting, and upscalers (ESRGAN, GFPGAN, CodeFormer), plus an extension ecosystem and support for NVIDIA, AMD, and Intel GPUs.
Hands-on lecture series that teaches neural networks from first principles up to building a GPT: each lecture pairs a YouTube video with Jupyter notebooks and exercises so you code models (micrograd → MLPs → WaveNet-like convs → GPT) while learning training and debugging.
AI Image2022
Unifies successive YOLO generations — YOLOv8, YOLO11, YOLOv3 and newer — under one package and a single `YOLO` API spanning detection, segmentation, classification, pose, oriented boxes and tracking, plus one-line export to ONNX, TensorRT and CoreML.
AI Audio2022
Multilingual sequence-to-sequence speech model and toolkit for speech recognition, speech-to-text translation, and language identification. Offers several model sizes (tiny → large/turbo) for different speed/accuracy trade-offs and ships with a CLI and Python API for offline transcription workflows.
AI Video2022
Generate a lip-synced talking-head video from a single portrait image and an audio clip using learned 3D motion coefficients for realistic expression and head motion. Offers still/reference modes, Colab/HuggingFace demos, and an Apache-2.0 license.
AI Audio2022
Alibaba DAMO Academy, Northwestern Polytechnical University (NWPU) +5Alibaba DAMO Academy, ModelScope
Bundles ASR, voice activity detection, punctuation, and speaker diarization into one pipeline, with pretrained models like Paraformer and SenseVoice. SenseVoice runs ~17x realtime on CPU; also ships streaming ASR and an OpenAI-compatible API.
AI Train2022
Reproduces GPT-2 (124M) from scratch on OpenWebText in ~4 days on an 8xA100 node, with the whole stack kept to two ~300-line files: train.py for the loop and model.py for the architecture. A char-level Shakespeare run finishes in ~3 minutes on one GPU.
AI Image2023
X-AnyLabeling is a powerful annotation tool integrated with an AI engine for fast and automatic labeling. Designed for multi-modal data engineers, it offers industrial-grade solutions for complex tasks. Supports images and videos, GPU acceleration, custom models, one-click inference for all task images, and import/export formats like COCO, VOC, YOLO. Handles classification, detection, segmentation, captioning, rotation, tracking, estimation, OCR, VQA, grounding, etc., with various annotation styles including polygons, rectangles, rotated boxes.
AI Train2023
Modular PyTorch-based framework for building, training, and deploying physics-informed ML models (neural operators, PINNs, GNNs, diffusion). Provides GPU‑optimized training, domain-specific datapipes for meshes/point clouds, distributed scaling and a model zoo.
AI Deploy2023
Open-source LLM inference and serving engine built around PagedAttention, which manages the KV cache like OS virtual memory to cut waste and raise throughput. Supports continuous batching, KV cache sharing, quantization, and an OpenAI-compatible API.
AI Train2023
Streamlines post-training and fine-tuning for large language and multimodal models with a single YAML-driven pipeline. Supports LoRA/QLoRA, full fine-tuning, preference tuning, RL methods, multi-GPU/FSDP/DeepSpeed, and many model backends (Hugging Face, local checkpoints).
AI Train2023
Connects a frozen vision encoder to a language model via visual instruction tuning, yielding an open multimodal assistant that follows image-grounded instructions. Released checkpoints span 7B-34B and approach GPT-4V on vision-language benchmarks.