A set of tools to visualize and interact with sequences of 3D data with cross-platform support on Windows, Linux, and macOS. It provides a native Python interface for loading and displaying SMPL[-H/-X], MANO, FLAME, STAR, and SUPR sequences in an interactive viewer. Users can render 3D data on top of images, edit SMPL sequences and poses, export screenshots and videos, and utilize a high-performance ModernGL-based rendering pipeline. The tool is designed for easy use and hacking, with features like headless mode, remote mode, animatable camera paths, and a built-in extensible GUI.

Only Train Once (OTO) is an automatic, architecture-agnostic DNN training and compression framework that allows users to train a general DNN from scratch or a pretrained checkpoint to achieve high performance and slimmer architecture simultaneously in a one-shot manner without fine-tuning. The framework includes features for automatic structured pruning and erasing operators, as well as hybrid structured sparse optimizers for efficient model compression. OTO provides tools for pruning zero-invariant group partitioning, constructing pruned models, and visualizing pruning and erasing dependency graphs. It supports the HESSO optimizer and offers a sanity check for compliance testing on various DNNs. The repository also includes publications, installation instructions, quick start guides, and a roadmap for future enhancements and collaborations.

Vision-LLM-Alignment is a repository focused on implementing alignment training for visual large language models (LLMs), including SFT training, reward model training, and PPO/DPO training. It supports various model architectures and provides datasets for training. The repository also offers benchmark results and installation instructions for users.

PyTorch Forecasting is a PyTorch-based package designed for state-of-the-art timeseries forecasting using deep learning architectures. It offers a high-level API and leverages PyTorch Lightning for efficient training on GPU or CPU with automatic logging. The package aims to simplify timeseries forecasting tasks by providing a flexible API for professionals and user-friendly defaults for beginners. It includes features such as a timeseries dataset class for handling data transformations, missing values, and subsampling, various neural network architectures optimized for real-world deployment, multi-horizon timeseries metrics, and hyperparameter tuning with optuna. Built on pytorch-lightning, it supports training on CPUs, single GPUs, and multiple GPUs out-of-the-box.

ProLLM is a framework that leverages Large Language Models to interpret and analyze protein sequences and interactions through natural language processing. It introduces the Protein Chain of Thought (ProCoT) method to transform complex protein interaction data into intuitive prompts, enhancing predictive accuracy by incorporating protein-specific embeddings and fine-tuning on domain-specific datasets.

Atom is an accurate low-bit weight-activation quantization algorithm that combines mixed-precision, fine-grained group quantization, dynamic activation quantization, KV-cache quantization, and efficient CUDA kernels co-design. It introduces a low-bit quantization method, Atom, to maximize Large Language Models (LLMs) serving throughput with negligible accuracy loss. The codebase includes evaluation of perplexity and zero-shot accuracy, kernel benchmarking, and end-to-end evaluation. Atom significantly boosts serving throughput by using low-bit operators and reduces memory consumption via low-bit quantization.

FATE-LLM is a framework supporting federated learning for large and small language models. It promotes training efficiency of federated LLMs using Parameter-Efficient methods, protects the IP of LLMs using FedIPR, and ensures data privacy during training and inference through privacy-preserving mechanisms.

E.D.D.I (Enhanced Dialog Driven Interface) is an enterprise-certified chatbot middleware that offers advanced prompt and conversation management for Conversational AI APIs. Developed in Java using Quarkus, it is lean, RESTful, scalable, and cloud-native. E.D.D.I is highly scalable and designed to efficiently manage conversations in AI-driven applications, with seamless API integration capabilities. Notable features include configurable NLP and Behavior rules, support for multiple chatbots running concurrently, and integration with MongoDB, OAuth 2.0, and HTML/CSS/JavaScript for UI. The project requires Java 21, Maven 3.8.4, and MongoDB >= 5.0 to run. It can be built as a Docker image and deployed using Docker or Kubernetes, with additional support for integration testing and monitoring through Prometheus and Kubernetes endpoints.

FlashInfer is a library for Language Languages Models that provides high-performance implementation of LLM GPU kernels such as FlashAttention, PageAttention and LoRA. FlashInfer focus on LLM serving and inference, and delivers state-the-art performance across diverse scenarios.

Tero Subtitler is an open source, cross-platform, and free subtitle editing software with a user-friendly interface. It offers fully fledged editing with SMPTE and MEDIA modes, support for various subtitle formats, multi-level undo/redo, search and replace, auto-backup, source and transcription modes, translation memory, audiovisual preview, timeline with waveform visualizer, manipulation tools, formatting options, quality control features, translation and transcription capabilities, validation tools, automation for correcting errors, and more. It also includes features like exporting subtitles to MP3, importing/exporting Blu-ray SUP format, generating blank video, generating video with hardcoded subtitles, video dubbing, and more. The tool utilizes powerful multimedia playback engines like mpv, advanced audio/video manipulation tools like FFmpeg, tools for automatic transcription like whisper.cpp/Faster-Whisper, auto-translation API like Google Translate, and ElevenLabs TTS for video dubbing.

DiagrammerGPT is an official implementation of a two-stage text-to-diagram generation framework that utilizes the layout guidance capabilities of LLMs to create accurate open-domain, open-platform diagrams. The tool first generates a diagram plan based on a prompt, which includes dense entities, fine-grained relationships, and precise layouts. Then, it refines the plan iteratively before generating the final diagram. DiagrammerGPT has been used to create various diagrams such as layers of the earth, Earth's position around the sun, and different types of rocks with labels.

Frigate Home Assistant Integration provides a rich media browser with thumbnails and navigation, sensor entities for camera FPS, detection FPS, process FPS, skipped FPS, and objects detected, binary sensor entities for object motion, camera entities for live view and object detected snapshot, switch entities for clips, detection, snapshots, and improve contrast, and support for multiple Frigate instances. It offers easy installation via HACS and manual installation options for advanced users. Users need to configure the `mqtt` integration for Frigate to work. Additionally, media browsing and a companion Lovelace card are available for enhanced user experience. Refer to the main Frigate documentation for detailed installation instructions and usage guidance.

NeMo Curator is a GPU-accelerated open-source framework designed for efficient large language model data curation. It provides scalable dataset preparation for tasks like foundation model pretraining, domain-adaptive pretraining, supervised fine-tuning, and parameter-efficient fine-tuning. The library leverages GPUs with Dask and RAPIDS to accelerate data curation, offering customizable and modular interfaces for pipeline expansion and model convergence. Key features include data download, text extraction, quality filtering, deduplication, downstream-task decontamination, distributed data classification, and PII redaction. NeMo Curator is suitable for curating high-quality datasets for large language model training.

Substrate is an open-source framework designed for human understanding, meaning, and progress. It provides a platform for individuals to contribute by modifying various object files such as Problems, Solutions, and Ideas. The project aims to visualize human progress and offers a web-based interface to facilitate non-coders in contributing. Substrate was created by Daniel Miessler in July 2024 and has a single-repo structure for easier project management. The tool emphasizes collaboration and inspiration from contributors like Jonathan Dunn, Joel Parish, and Joseph Thacker.

Burr is a Python library and UI that makes it easy to develop applications that make decisions based on state (chatbots, agents, simulations, etc...). Burr includes a UI that can track/monitor those decisions in real time.

Shards is a high-performance, multi-platform, type-safe programming language designed for visual development. It is a dataflow visual programming language that enables building full-fledged apps and games without traditional coding. Shards features automatic type checking, optimized shard implementations for high performance, and an intuitive visual workflow for beginners. The language allows seamless round-trip engineering between code and visual models, empowering users to create multi-platform apps easily. Shards also powers an upcoming AI-powered game creation system, enabling real-time collaboration and game development in a low to no-code environment.

Cog-comfyui allows users to run ComfyUI workflows on Replicate. ComfyUI is a visual programming tool for creating and sharing generative art workflows. With cog-comfyui, users can access a variety of pre-trained models and custom nodes to create their own unique artworks. The tool is easy to use and does not require any coding experience. Users simply need to upload their API JSON file and any necessary input files, and then click the "Run" button. Cog-comfyui will then generate the output image or video file.

Deforum for ComfyUI is an integration tool designed to enhance the user experience of using ComfyUI. It provides custom nodes that can be added to ComfyUI to improve functionality and workflow. Users can easily install Deforum for ComfyUI by cloning the repository and following the provided instructions. The tool is compatible with Python v3.10 and is recommended to be used within a virtual environment. Contributions to the tool are welcome, and users can join the Discord community for support and discussions.

Anim v0.1.0 is an animation tool that allows users to convert videos to animations using mixamorig characters. It features FK animation editing, object selection, embedded Python support (only on Windows), and the ability to export to glTF and FBX formats. Users can also utilize Mediapipe to create animations. The tool is designed to assist users in creating animations with ease and flexibility.

Next Money Stripe Starter is a SaaS Starter project that empowers your next project with a stack of Next.js, Prisma, Supabase, Clerk Auth, Resend, React Email, Shadcn/ui, and Stripe. It seamlessly integrates these technologies to accelerate your development and SaaS journey. The project includes frameworks, platforms, UI components, hooks and utilities, code quality tools, and miscellaneous features to enhance the development experience. Created by @koyaguo in 2023 and released under the MIT license.

A set of tools to visualize and interact with sequences of 3D data with cross-platform support on Windows, Linux, and macOS. It provides a native Python interface for loading and displaying SMPL[-H/-X], MANO, FLAME, STAR, and SUPR sequences in an interactive viewer. Users can render 3D data on top of images, edit SMPL sequences and poses, export screenshots and videos, and utilize a high-performance ModernGL-based rendering pipeline. The tool is designed for easy use and hacking, with features like headless mode, remote mode, animatable camera paths, and a built-in extensible GUI.

A set of tools to visualize and interact with sequences of 3D data with cross-platform support on Windows, Linux, and macOS. It provides a native Python interface for loading and displaying SMPL[-H/-X], MANO, FLAME, STAR, and SUPR sequences in an interactive viewer. Users can render 3D data on top of images, edit SMPL sequences and poses, export screenshots and videos, and utilize a high-performance ModernGL-based rendering pipeline. The tool is designed for easy use and hacking, with features like headless mode, remote mode, animatable camera paths, and a built-in extensible GUI.

SPEAR (Simulator for Photorealistic Embodied AI Research) is a powerful tool for training embodied agents. It features 300 unique virtual indoor environments with 2,566 unique rooms and 17,234 unique objects that can be manipulated individually. Each environment is designed by a professional artist and features detailed geometry, photorealistic materials, and a unique floor plan and object layout. SPEAR is implemented as Unreal Engine assets and provides an OpenAI Gym interface for interacting with the environments via Python.

OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference. It provides a common API to deliver inference solutions on various platforms, including CPU, GPU, NPU, and heterogeneous devices. OpenVINO™ supports pre-trained models from Open Model Zoo and popular frameworks like TensorFlow, PyTorch, and ONNX. Key components of OpenVINO™ include the OpenVINO™ Runtime, plugins for different hardware devices, frontends for reading models from native framework formats, and the OpenVINO Model Converter (OVC) for adjusting models for optimal execution on target devices.

PEFT (Parameter-Efficient Fine-Tuning) is a collection of state-of-the-art methods that enable efficient adaptation of large pretrained models to various downstream applications. By only fine-tuning a small number of extra model parameters instead of all the model's parameters, PEFT significantly decreases the computational and storage costs while achieving performance comparable to fully fine-tuned models.

This repo hosts tutorial documentation for running generative AI models on NVIDIA Jetson devices. The documentation is auto-generated and hosted on GitHub Pages using their CI/CD feature to automatically generate/update the HTML documentation site upon new commits.

Emgu CV is a cross-platform .Net wrapper for the OpenCV image-processing library. It allows OpenCV functions to be called from .NET compatible languages. The wrapper can be compiled by Visual Studio, Unity, and "dotnet" command, and it can run on Windows, Mac OS, Linux, iOS, and Android.

MMStar is an elite vision-indispensable multi-modal benchmark comprising 1,500 challenge samples meticulously selected by humans. It addresses two key issues in current LLM evaluation: the unnecessary use of visual content in many samples and the existence of unintentional data leakage in LLM and LVLM training. MMStar evaluates 6 core capabilities across 18 detailed axes, ensuring a balanced distribution of samples across all dimensions.

VLMEvalKit is an open-source evaluation toolkit of large vision-language models (LVLMs). It enables one-command evaluation of LVLMs on various benchmarks, without the heavy workload of data preparation under multiple repositories. In VLMEvalKit, we adopt generation-based evaluation for all LVLMs, and provide the evaluation results obtained with both exact matching and LLM-based answer extraction.