MLX-VLM is a package designed for running Vision LLMs on Mac systems using MLX. It provides a convenient way to install and utilize the package for processing large language models related to vision tasks. The tool simplifies the process of running LLMs on Mac computers, offering a seamless experience for users interested in leveraging MLX for vision-related projects.

The GenAI repository contains pipelines that implement image and text generation tasks. The implementation uses OpenVINO capabilities to optimize the pipelines. Each sample covers a family of models and suggests certain modifications to adapt the code to specific needs. It includes the following pipelines: 1. Benchmarking script for large language models 2. Text generation C++ samples that support most popular models like LLaMA 2 3. Stable Diffuison (with LoRA) C++ image generation pipeline 4. Latent Consistency Model (with LoRA) C++ image generation pipeline

J.A.R.V.I.S (Just A Rather Very Intelligent System) is an advanced AI assistant inspired by Iron Man's Jarvis, designed to assist with various tasks, from navigating websites to controlling your PC with natural language commands.

Smile (Statistical Machine Intelligence and Learning Engine) is a comprehensive machine learning, NLP, linear algebra, graph, interpolation, and visualization system in Java and Scala. It covers every aspect of machine learning, including classification, regression, clustering, association rule mining, feature selection, manifold learning, multidimensional scaling, genetic algorithms, missing value imputation, efficient nearest neighbor search, etc. Smile implements major machine learning algorithms and provides interactive shells for Java, Scala, and Kotlin. It supports model serialization, data visualization using SmilePlot and declarative approach, and offers a gallery showcasing various algorithms and visualizations.

The 'understand-r1-zero' repository focuses on understanding R1-Zero-like training from a critical perspective. It provides insights into base models and reinforcement learning components, highlighting findings and proposing solutions for biased optimization. The repository offers a minimalist recipe for R1-Zero training, detailing the RL-tuning process and achieving state-of-the-art performance with minimal compute resources. It includes codebase, models, and paper related to R1-Zero training implemented with the Oat framework, emphasizing research-friendly and efficient LLM RL techniques.

This Code Interpreter SDK allows you to run AI-generated Python code and each run share the context. That means that subsequent runs can reference to variables, definitions, etc from past code execution runs. The code interpreter runs inside the E2B Sandbox - an open-source secure micro VM made for running untrusted AI-generated code and AI agents. - ✅ Works with any LLM and AI framework - ✅ Supports streaming content like charts and stdout, stderr - ✅ Python & JS SDK - ✅ Runs on serverless and edge functions - ✅ 100% open source (including infrastructure)

ChatTTS is a generative speech model optimized for dialogue scenarios, providing natural and expressive speech synthesis with fine-grained control over prosodic features. It supports multiple speakers and surpasses most open-source TTS models in terms of prosody. The model is trained with 100,000+ hours of Chinese and English audio data, and the open-source version on HuggingFace is a 40,000-hour pre-trained model without SFT. The roadmap includes open-sourcing additional features like VQ encoder, multi-emotion control, and streaming audio generation. The tool is intended for academic and research use only, with precautions taken to limit potential misuse.

Vim-airline is a lean and mean status/tabline plugin for Vim that provides a nice statusline at the bottom of each Vim window. It consists of several sections displaying information such as mode, environment status, filename, filetype, file encoding, and current position in the file. The plugin is highly customizable and integrates with various plugins, providing a tiny core with extensibility in mind. It is optimized for speed, supports multiple themes, and integrates seamlessly with other plugins. Vim-airline is written in 100% Vimscript, eliminating the need for Python. The plugin aims to be stable and includes a unit testing suite for reliability.

Scikit-LLM is a tool that seamlessly integrates powerful language models like ChatGPT into scikit-learn for enhanced text analysis tasks. It allows users to leverage large language models for various text analysis applications within the familiar scikit-learn framework. The tool simplifies the process of incorporating advanced language processing capabilities into machine learning pipelines, enabling users to benefit from the latest advancements in natural language processing.

JetStream is a throughput and memory optimized engine for LLM inference on XLA devices, starting with TPUs (and GPUs in future -- PRs welcome). It is designed to provide high performance and scalability for large language models, enabling efficient inference on cloud-based TPUs. JetStream leverages XLA to optimize the execution of LLM models, resulting in faster and more efficient inference. Additionally, JetStream supports quantization techniques to further enhance performance and reduce memory consumption. By utilizing JetStream, developers can deploy and run LLM models on TPUs with ease, achieving optimal performance and cost-effectiveness.

VideoTuna is a codebase for text-to-video applications that integrates multiple AI video generation models for text-to-video, image-to-video, and text-to-image generation. It provides comprehensive pipelines in video generation, including pre-training, continuous training, post-training, and fine-tuning. The models in VideoTuna include U-Net and DiT architectures for visual generation tasks, with upcoming releases of a new 3D video VAE and a controllable facial video generation model.

Infinity is a high-throughput, low-latency REST API for serving vector embeddings, supporting all sentence-transformer models and frameworks. It is developed under the MIT License and powers inference behind Gradient.ai. The API allows users to deploy models from SentenceTransformers, offers fast inference backends utilizing various accelerators, dynamic batching for efficient processing, correct and tested implementation, and easy-to-use API built on FastAPI with Swagger documentation. Users can embed text, rerank documents, and perform text classification tasks using the tool. Infinity supports various models from Huggingface and provides flexibility in deployment via CLI, Docker, Python API, and cloud services like dstack. The tool is suitable for tasks like embedding, reranking, and text classification.

BrowserGym is an open, easy-to-use, and extensible framework designed to accelerate web agent research. It provides benchmarks like MiniWoB, WebArena, VisualWebArena, WorkArena, AssistantBench, and WebLINX. Users can design new web benchmarks by inheriting the AbstractBrowserTask class. The tool allows users to install different packages for core functionalities, experiments, and specific benchmarks. It supports the development setup and offers boilerplate code for running agents on various tasks. BrowserGym is not a consumer product and should be used with caution.

VinAI_Translate is a Vietnamese-English Neural Machine Translation System offering state-of-the-art text-to-text translation models for Vietnamese-to-English and English-to-Vietnamese. The system includes pre-trained models with different configurations and parameters, allowing for further fine-tuning. Users can interact with the models through the VinAI Translate system website or the HuggingFace space 'VinAI Translate'. Evaluation scripts are available for assessing the translation quality. The tool can be used in the 'transformers' library for Vietnamese-to-English and English-to-Vietnamese translations, supporting both GPU-based batch translation and CPU-based sequence translation examples.

Evalverse is an open-source project designed to support Large Language Model (LLM) evaluation needs. It provides a standardized and user-friendly solution for processing and managing LLM evaluations, catering to AI research engineers and scientists. Evalverse supports various evaluation methods, insightful reports, and no-code evaluation processes. Users can access unified evaluation with submodules, request evaluations without code via Slack bot, and obtain comprehensive reports with scores, rankings, and visuals. The tool allows for easy comparison of scores across different models and swift addition of new evaluation tools.

Rill Flow is a high-performance, scalable distributed workflow orchestration service that supports the execution of tens of millions of tasks per day with task execution latency less than 100ms. It is distributed and supports the orchestration and scheduling of heterogeneous distributed systems. Rill Flow is easy to use, supporting visual process orchestration and plug-in access. It is cloud native, allowing for cloud native container deployment and cloud native function orchestration. Additionally, Rill Flow supports rapid integration of LLM model services.

Hyper-Pretrained Transformers (HPT) is a novel multimodal LLM framework from HyperGAI, trained for vision-language models capable of understanding both textual and visual inputs. The repository contains the open-source implementation of inference code to reproduce the evaluation results of HPT Air on different benchmarks. HPT has achieved competitive results with state-of-the-art models on various multimodal LLM benchmarks. It offers models like HPT 1.5 Air and HPT 1.0 Air, providing efficient solutions for vision-and-language tasks.

LearnOpenCV is a repository containing code for Computer Vision, Deep learning, and AI research articles shared on the blog LearnOpenCV.com. It serves as a resource for individuals looking to enhance their expertise in AI through various courses offered by OpenCV. The repository includes a wide range of topics such as image inpainting, instance segmentation, robotics, deep learning models, and more, providing practical implementations and code examples for readers to explore and learn from.

Spark AI Free 服务 provides high-speed streaming output, multi-turn dialogue support, AI drawing support, long document interpretation, and image parsing. It offers zero-configuration deployment, multi-token support, and automatic session trace cleaning. It is fully compatible with the ChatGPT interface. The repository includes multiple free-api projects for various AI services. Users can access the API for tasks such as chat completions, AI drawing, document interpretation, image analysis, and ssoSessionId live checking. The project also provides guidelines for deployment using Docker, Docker-compose, Render, Vercel, and native deployment methods. It recommends using custom clients for faster and simpler access to the free-api series projects.

MLX-VLM is a package designed for running Vision LLMs on Mac systems using MLX. It provides a convenient way to install and utilize the package for processing large language models related to vision tasks. The tool simplifies the process of running LLMs on Mac computers, offering a seamless experience for users interested in leveraging MLX for vision-related projects.

This is the official Clarifai gRPC Python client for interacting with their recognition API. Clarifai offers a platform for data scientists, developers, researchers, and enterprises to utilize artificial intelligence for image, video, and text analysis through computer vision and natural language processing. The client allows users to authenticate, predict concepts in images, and access various functionalities provided by the Clarifai API. It follows a versioning scheme that aligns with the backend API updates and includes specific instructions for installation and troubleshooting. Users can explore the Clarifai demo, sign up for an account, and refer to the documentation for detailed information.

This repository provides the latest implementation for the AI Horde Worker, allowing users to utilize their graphics card(s) to generate, post-process, or analyze images for others. It offers a platform where users can create images and earn 'kudos' in return, granting priority for their own image generations. The repository includes important details for setup, recommendations for system configurations, instructions for installation on Windows and Linux, basic usage guidelines, and information on updating the AI Horde Worker. Users can also run the worker with multiple GPUs and receive notifications for updates through Discord. Additionally, the repository contains models that are licensed under the CreativeML OpenRAIL License.

Geospy is a Python tool that utilizes Graylark's AI-powered geolocation service to determine the location where photos were taken. It allows users to analyze images and retrieve information such as country, city, explanation, coordinates, and Google Maps links. The tool provides a seamless way to integrate geolocation services into various projects and applications.

Awesome-Colorful-LLM is a meticulously assembled anthology of vibrant multimodal research focusing on advancements propelled by large language models (LLMs) in domains such as Vision, Audio, Agent, Robotics, and Fundamental Sciences like Mathematics. The repository contains curated collections of works, datasets, benchmarks, projects, and tools related to LLMs and multimodal learning. It serves as a comprehensive resource for researchers and practitioners interested in exploring the intersection of language models and various modalities for tasks like image understanding, video pretraining, 3D modeling, document understanding, audio analysis, agent learning, robotic applications, and mathematical research.

**Prompt flow** is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.

DeepEval is a simple-to-use, open-source LLM evaluation framework specialized for unit testing LLM outputs. It incorporates various metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., and runs locally on your machine for evaluation. It provides a wide range of ready-to-use evaluation metrics, allows for creating custom metrics, integrates with any CI/CD environment, and enables benchmarking LLMs on popular benchmarks. DeepEval is designed for evaluating RAG and fine-tuning applications, helping users optimize hyperparameters, prevent prompt drifting, and transition from OpenAI to hosting their own Llama2 with confidence.

MegaDetector is an AI model that identifies animals, people, and vehicles in camera trap images (which also makes it useful for eliminating blank images). This model is trained on several million images from a variety of ecosystems. MegaDetector is just one of many tools that aims to make conservation biologists more efficient with AI. If you want to learn about other ways to use AI to accelerate camera trap workflows, check out our of the field, affectionately titled "Everything I know about machine learning and camera traps".

LeapfrogAI is a self-hosted AI platform designed to be deployed in air-gapped resource-constrained environments. It brings sophisticated AI solutions to these environments by hosting all the necessary components of an AI stack, including vector databases, model backends, API, and UI. LeapfrogAI's API closely matches that of OpenAI, allowing tools built for OpenAI/ChatGPT to function seamlessly with a LeapfrogAI backend. It provides several backends for various use cases, including llama-cpp-python, whisper, text-embeddings, and vllm. LeapfrogAI leverages Chainguard's apko to harden base python images, ensuring the latest supported Python versions are used by the other components of the stack. The LeapfrogAI SDK provides a standard set of protobuffs and python utilities for implementing backends and gRPC. LeapfrogAI offers UI options for common use-cases like chat, summarization, and transcription. It can be deployed and run locally via UDS and Kubernetes, built out using Zarf packages. LeapfrogAI is supported by a community of users and contributors, including Defense Unicorns, Beast Code, Chainguard, Exovera, Hypergiant, Pulze, SOSi, United States Navy, United States Air Force, and United States Space Force.

This Docker image for LLaVA (Large Language and Vision Assistant) provides a convenient way to run LLaVA locally or on RunPod. LLaVA is a powerful AI tool that combines natural language processing and computer vision capabilities. With this Docker image, you can easily access LLaVA's functionalities for various tasks, including image captioning, visual question answering, text summarization, and more. The image comes pre-installed with LLaVA v1.2.0, Torch 2.1.2, xformers 0.0.23.post1, and other necessary dependencies. You can customize the model used by setting the MODEL environment variable. The image also includes a Jupyter Lab environment for interactive development and exploration. Overall, this Docker image offers a comprehensive and user-friendly platform for leveraging LLaVA's capabilities.

The 'carrot' repository on GitHub provides a list of free and user-friendly ChatGPT mirror sites for easy access. The repository includes sponsored sites offering various GPT models and services. Users can find and share sites, report errors, and access stable and recommended sites for ChatGPT usage. The repository also includes a detailed list of ChatGPT sites, their features, and accessibility options, making it a valuable resource for ChatGPT users seeking free and unlimited GPT services.

TrustLLM is a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions. Specifically, we first propose a set of principles for trustworthy LLMs that span eight different dimensions. Based on these principles, we further establish a benchmark across six dimensions including truthfulness, safety, fairness, robustness, privacy, and machine ethics. We then present a study evaluating 16 mainstream LLMs in TrustLLM, consisting of over 30 datasets. The document explains how to use the trustllm python package to help you assess the performance of your LLM in trustworthiness more quickly. For more details about TrustLLM, please refer to project website.

AI-YinMei is an AI virtual anchor Vtuber development tool (N card version). It supports fastgpt knowledge base chat dialogue, a complete set of solutions for LLM large language models: [fastgpt] + [one-api] + [Xinference], supports docking bilibili live broadcast barrage reply and entering live broadcast welcome speech, supports Microsoft edge-tts speech synthesis, supports Bert-VITS2 speech synthesis, supports GPT-SoVITS speech synthesis, supports expression control Vtuber Studio, supports painting stable-diffusion-webui output OBS live broadcast room, supports painting picture pornography public-NSFW-y-distinguish, supports search and image search service duckduckgo (requires magic Internet access), supports image search service Baidu image search (no magic Internet access), supports AI reply chat box [html plug-in], supports AI singing Auto-Convert-Music, supports playlist [html plug-in], supports dancing function, supports expression video playback, supports head touching action, supports gift smashing action, supports singing automatic start dancing function, chat and singing automatic cycle swing action, supports multi scene switching, background music switching, day and night automatic switching scene, supports open singing and painting, let AI automatically judge the content.