Detects, segments, and tracks every instance of an open-vocabulary concept in images and video from a text phrase or visual exemplar, not just one object per prompt. An 848M-param model reaching ~75-80% of human accuracy across 270K concepts.
A 20B-parameter MMDiT diffusion model that generates and edits images with accurate embedded text, including dense Chinese and English typography. Handles complex multi-line layouts and identity-preserving edits while keeping text legible.
Self-supervised vision foundation model producing dense, patch-level features that transfer to classification, segmentation, depth, and detection with a frozen backbone. Spans ViT-S (21M) to ViT-7B (6.7B params), plus ConvNeXt and satellite variants.
Framework for building multi-modal AI agents that watch, listen, and reason over live video, pairing vision models (YOLO, Roboflow, Moondream) with LLMs like Gemini and OpenAI. Agents join calls in ~500ms and keep audio/video latency under 30ms.
Generates and edits full-length music locally using a hybrid language-model planner and a diffusion transformer. Provides text- and audio-driven song synthesis plus selective editing (cover generation, repainting, vocal→BGM), metadata control and lightweight LoRA personalization, and runs on consumer GPUs/CPUs.
Generates explorable, 3D-consistent virtual worlds from a single image or short video. Includes official implementations of Lyra‑1 (feed‑forward 3D/4D scene generation via video-diffusion self-distillation) and Lyra‑2 (long-horizon, explorable generative 3D worlds). Best for research and creative prototyping; requires substantial GPU compute.
Automatically removes safety alignment from transformer LLMs via directional ablation, with Optuna's TPE optimizer tuning the parameters — no retraining or model-internals expertise needed; hit 3/100 refusals at 0.16 KL on Gemma-3-12b.
Provides an NVFP4‑optimized training and inference infrastructure for long-form video diffusion models — supports multi-shot AR training, KV-cache and NVFP4 quantized inference, sequence-parallelism and async decoding for higher FPS and longer outputs.
Provides a Gymnasium-style API and tooling to create, deploy, and interact with isolated execution environments for agentic RL training. Includes async/sync clients, a web interface, CLI, Docker-based deployment, and Hugging Face Spaces integration.
Converts images and PDFs into structured Markdown, HTML, or JSON while preserving layout, handling tables, math, handwriting, charts, and chemistry diagrams across 90+ languages. Runs locally via HuggingFace or against a vLLM server.
Curated collection of 70 hands‑on cybersecurity projects, certification roadmaps and learning resources organized into Foundations/Beginner/Intermediate/Advanced tiers. Each project ships source code plus deep learn/ documentation; several focus on AI security (LLM prompt defenses, ML threat detection).
Delivers multilingual, on-device text-to-speech via ONNX Runtime with prebuilt ONNX assets and cross-platform SDKs (Python, Node, mobile); targets low-latency, privacy-preserving TTS with ready demos and 31-language support in v3.