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Readable, minimal-dependency Python implementations of core robotics algorithms — localization (EKF, particle filter), SLAM (ICP, FastSLAM), path planning (A*, RRT*, PRM), and path tracking (LQR, MPC) — written to be studied, not just run.
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.
Reference implementation for Stability AI's diffusion models: SDXL base/refiner/Turbo for text-to-image, plus Stable Video Diffusion, SV3D, and SV4D for image-to-video and 4D synthesis. A modular engine separates samplers, guiders, and conditioners.
Runs Stable Diffusion XL behind a Midjourney-style interface, hiding samplers, model swaps, and LoRA weights. A built-in GPT2 expander rewrites prompts into richer styling, and it works fully offline on as little as 4GB of Nvidia VRAM.
Runnable Jupyter notebooks for building with the Claude API: tool use, RAG, vision, prompt caching, sub-agents, classification, summarization, and integrations like Pinecone and Voyage embeddings. Copy-paste recipes that drop into real projects.
Browser-based editor for inspecting, editing, optimizing and publishing 3D Gaussian splats. Runs entirely in the browser with live preview, localization support, and export/publishing workflows — no install required, aimed at quick iteration and lightweight delivery.
Collection of runnable model implementations — LLaMA, Mistral, Stable Diffusion, Whisper, CLIP, plus LoRA fine-tuning — ported to the MLX array framework so they run natively on Apple silicon's unified memory rather than CUDA.
Curated developer resources that demonstrate building RAG systems, multi-agent workflows, and memory-augmented AI using Oracle AI Database and OCI — includes end-to-end reference apps, notebooks, guides, and workshops for hands-on prototyping.
Chains pre-trained AI weather and climate models like GraphCast, Pangu, and FourCastNet into composable inference pipelines. Swap prognostic or diagnostic components, plug in reanalysis sources, and add ensemble perturbations or in-loop metrics.
Turns PDFs and images into clean Markdown with a 7B vision-language model, keeping tables, equations, handwriting, and multi-column reading order while removing headers and footers. Runs on one 12GB+ GPU at about 1/32 the cost of GPT-4o APIs.
Generates video from text or images via a DiT-based latent diffusion model: text-to-video, image-to-video, frame extension, and multi-keyframe conditioning in one model. A distilled 2B variant runs near real-time on one H100; 13B for higher quality.