Best AI tools for< Model Averaging >

Enhans AI Model Generator is an advanced AI tool designed to help users generate AI models efficiently. It utilizes cutting-edge algorithms and machine learning techniques to streamline the model creation process. With Enhans AI Model Generator, users can easily input their data, select the desired parameters, and obtain a customized AI model tailored to their specific needs. The tool is user-friendly and does not require extensive programming knowledge, making it accessible to a wide range of users, from beginners to experts in the field of AI.

The Frontier Model Forum (FMF) is a collaborative effort among leading AI companies to advance AI safety and responsibility. The FMF brings together technical and operational expertise to identify best practices, conduct research, and support the development of AI applications that meet society's most pressing needs. The FMF's core objectives include advancing AI safety research, identifying best practices, collaborating across sectors, and helping AI meet society's greatest challenges.

AI Model Agency is a cutting-edge AI fashion modeling agency that offers AI-generated virtual influencers, fashion model generator, and AI-driven fashion solutions. The agency revolutionizes fashion photography by blending technology and creativity to provide innovative synthetic photography and video services. With a focus on empowering brands with AI brilliance, AI Model Agency helps businesses stay ahead of the curve in the ever-evolving fashion industry.

Role Model AI is a revolutionary multi-dimensional assistant that combines practicality and innovation. It offers four dynamic interfaces for seamless interaction: phone calls for on-the-go assistance, an interactive agent dashboard for detailed task management, lifelike 3D avatars for immersive communication, and an engaging Fortnite world integration for a gaming-inspired experience. Role Model AI adapts to your lifestyle, blending seamlessly into your personal and professional worlds, providing unparalleled convenience and a unique, versatile solution for managing tasks and interactions.

Flux LoRA Model Library is an AI tool that provides a platform for finding and using Flux LoRA models suitable for various projects. Users can browse a catalog of popular Flux LoRA models and learn about FLUX models and LoRA (Low-Rank Adaptation) technology. The platform offers resources for fine-tuning models and ensuring responsible use of generated images.

OpenAI Strawberry Model is a cutting-edge AI initiative that represents a significant leap in AI capabilities, focusing on enhancing reasoning, problem-solving, and complex task execution. It aims to improve AI's ability to handle mathematical problems, programming tasks, and deep research, including long-term planning and action. The project showcases advancements in AI safety and aims to reduce errors in AI responses by generating high-quality synthetic data for training future models. Strawberry is designed to achieve human-like reasoning and is expected to play a crucial role in the development of OpenAI's next major model, codenamed 'Orion.'

HUAWEI Cloud Pangu is an AI tool designed for accelerating drug discovery by optimizing drug molecules. It offers features such as Molecule Search, Molecule Optimizer, and Pocket Molecule Design. Users can submit molecules for optimization and view historical optimization results. The tool is based on the MindSpore framework and has been visited over 300,000 times since August 23, 2021.

LiteLLM is a platform that provides model access, logging, and usage tracking across various LLMs in the OpenAI format. It offers features such as control over model access, budget tracking, pass-through endpoints for migration, OpenAI-compatible API access, and a self-serve portal for key management. LiteLLM also offers different pricing tiers, including Open Source, Enterprise Basic, and Enterprise Premium, with various integrations and features tailored for different user needs.

Sapling is a language model copilot and API for businesses. It provides real-time suggestions to help sales, support, and success teams more efficiently compose personalized responses. Sapling also offers a variety of features to help businesses improve their customer service, including: * Autocomplete Everywhere: Provides deep learning-powered autocomplete suggestions across all messaging platforms, allowing agents to compose replies more quickly. * Sapling Suggest: Retrieves relevant responses from a team response bank and allows agents to respond more quickly to customer inquiries by simply clicking on suggested responses in real time. * Snippet macros: Allow for quick insertion of common responses. * Grammar and language quality improvements: Sapling catches 60% more language quality issues than other spelling and grammar checkers using a machine learning system trained on millions of English sentences. * Enterprise teams can define custom settings for compliance and content governance. * Distribute knowledge: Ensure team knowledge is shared in a snippet library accessible on all your web applications. * Perform blazing fast search on your knowledge library for compliance, upselling, training, and onboarding.

Meshy AI is the #1 AI 3D Model Generator for Creators, offering powerful AI generation tools to help users unlock infinite possibilities. It allows users to create detailed 3D models from simple text prompts, turn artwork and images into 3D models, generate textures for existing 3D models, and create rigged and animated 3D characters with ease. Meshy is trusted by millions of game developers, studios, 3D printing enthusiasts, and XR creators worldwide for its speed, ease of use, and realistic results.

VModel.AI is an AI fashion models generator that revolutionizes on-model photography for fashion retailers. It utilizes artificial intelligence to create high-quality on-model photography without the need for elaborate photoshoots, reducing model photography costs by 90%. The tool helps diversify stores, improve E-commerce engagement, reduce returns, promote diversity and inclusion in fashion, and enhance product offerings.

UbiOps is an AI infrastructure platform that helps teams quickly run their AI & ML workloads as reliable and secure microservices. It offers powerful AI model serving and orchestration with unmatched simplicity, speed, and scale. UbiOps allows users to deploy models and functions in minutes, manage AI workloads from a single control plane, integrate easily with tools like PyTorch and TensorFlow, and ensure security and compliance by design. The platform supports hybrid and multi-cloud workload orchestration, rapid adaptive scaling, and modular applications with unique workflow management system.

Phenaki is a model capable of generating realistic videos from a sequence of textual prompts. It is particularly challenging to generate videos from text due to the computational cost, limited quantities of high-quality text-video data, and variable length of videos. To address these issues, Phenaki introduces a new causal model for learning video representation, which compresses the video to a small representation of discrete tokens. This tokenizer uses causal attention in time, which allows it to work with variable-length videos. To generate video tokens from text, Phenaki uses a bidirectional masked transformer conditioned on pre-computed text tokens. The generated video tokens are subsequently de-tokenized to create the actual video. To address data issues, Phenaki demonstrates how joint training on a large corpus of image-text pairs as well as a smaller number of video-text examples can result in generalization beyond what is available in the video datasets. Compared to previous video generation methods, Phenaki can generate arbitrarily long videos conditioned on a sequence of prompts (i.e., time-variable text or a story) in an open domain. To the best of our knowledge, this is the first time a paper studies generating videos from time-variable prompts. In addition, the proposed video encoder-decoder outperforms all per-frame baselines currently used in the literature in terms of spatio-temporal quality and the number of tokens per video.

Artiko.ai is a multi-model AI chat platform that integrates advanced AI models such as ChatGPT, Claude 3, Gemini 1.5, and Mistral AI. It offers a convenient and cost-effective solution for work, business, or study by providing a single chat interface to harness the power of multi-model AI. Users can save time and money while achieving better results through features like text rewriting, data conversation, AI assistants, website chatbot, PDF and document chat, translation, brainstorming, and integration with various tools like Woocommerce, Amazon, Salesforce, and more.

Claude is a large multi-modal model, trained by Google. It is similar to GPT-3, but it is trained on a larger dataset and with more advanced techniques. Claude is capable of generating human-like text, translating languages, answering questions, and writing different kinds of creative content.

SuperAnnotate is an AI data platform that simplifies and accelerates model-building by unifying the AI pipeline. It enables users to create, curate, and evaluate datasets efficiently, leading to the development of better models faster. The platform offers features like connecting any data source, building customizable UIs, creating high-quality datasets, evaluating models, and deploying models seamlessly. SuperAnnotate ensures global security and privacy measures for data protection.

GPT4All is a web-based platform that allows users to access the GPT-4 language model. GPT-4 is a large language model that can be used for a variety of tasks, including text generation, translation, question answering, and code generation. GPT4All makes it easy for users to get started with GPT-4, without having to worry about the technical details of setting up and running the model.

Weights & Biases is an AI tool that offers documentation, guides, tutorials, and support for using AI models in applications. The platform provides two main products: W&B Weave for integrating AI models into code and W&B Models for building custom AI models. Users can access features such as tracing, output evaluation, cost estimates, hyperparameter sweeps, model registry, and more. Weights & Biases aims to simplify the process of working with AI models and improving model reproducibility.

Unsloth is an AI tool designed to make finetuning large language models like Llama-3, Mistral, Phi-3, and Gemma 2x faster, use 70% less memory, and with no degradation in accuracy. The tool provides documentation to help users navigate through training their custom models, covering essentials such as installing and updating Unsloth, creating datasets, running, and deploying models. Users can also integrate third-party tools and utilize platforms like Google Colab.

Inspect is an open-source framework for large language model evaluations created by the UK AI Safety Institute. It provides built-in components for prompt engineering, tool usage, multi-turn dialog, and model graded evaluations. Users can explore various solvers, tools, scorers, datasets, and models to create advanced evaluations. Inspect supports extensions for new elicitation and scoring techniques through Python packages.

A comprehensive repository focusing on 'Model Merging in LLMs, MLLMs, and Beyond', providing an exhaustive overview of model merging methods, theories, applications, and future research directions. The repository covers various advanced methods, applications in foundation models, different machine learning subfields, and tasks like pre-merging methods, architecture transformation, weight alignment, basic merging methods, and more.

ERAG is an advanced system that combines lexical, semantic, text, and knowledge graph searches with conversation context to provide accurate and contextually relevant responses. This tool processes various document types, creates embeddings, builds knowledge graphs, and uses this information to answer user queries intelligently. It includes modules for interacting with web content, GitHub repositories, and performing exploratory data analysis using various language models.

Mergekit is a toolkit for merging pre-trained language models. It uses an out-of-core approach to perform unreasonably elaborate merges in resource-constrained situations. Merges can be run entirely on CPU or accelerated with as little as 8 GB of VRAM. Many merging algorithms are supported, with more coming as they catch my attention.

Efficient Foundation Model Survey is a comprehensive analysis of resource-efficient large language models (LLMs) and multimodal foundation models. The survey covers algorithmic and systemic innovations to support the growth of large models in a scalable and environmentally sustainable way. It explores cutting-edge model architectures, training/serving algorithms, and practical system designs. The goal is to provide insights on tackling resource challenges posed by large foundation models and inspire future breakthroughs in the field.

PyCM is a Python library for multi-class confusion matrices, providing support for input data vectors and direct matrices. It is a comprehensive tool for post-classification model evaluation, offering a wide range of metrics for predictive models and accurate evaluation of various classifiers. PyCM is designed for data scientists who require diverse metrics for their models.

MME-RealWorld is a benchmark designed to address real-world applications with practical relevance, featuring 13,366 high-resolution images and 29,429 annotations across 43 tasks. It aims to provide substantial recognition challenges and overcome common barriers in existing Multimodal Large Language Model benchmarks, such as small data scale, restricted data quality, and insufficient task difficulty. The dataset offers advantages in data scale, data quality, task difficulty, and real-world utility compared to existing benchmarks. It also includes a Chinese version with additional images and QA pairs focused on Chinese scenarios.

AlphaFold3 is an implementation of the Alpha Fold 3 model in PyTorch for accurate structure prediction of biomolecular interactions. It includes modules for genetic diffusion and full model examples for forward pass computations. The tool allows users to generate random pair and single representations, operate on atomic coordinates, and perform structure predictions based on input tensors. The implementation also provides functionalities for training and evaluating the model.

The 'gritlm' repository provides all materials for the paper Generative Representational Instruction Tuning. It includes code for inference, training, evaluation, and known issues related to the GritLM model. The repository also offers models for embedding and generation tasks, along with instructions on how to train and evaluate the models. Additionally, it contains visualizations, acknowledgements, and a citation for referencing the work.

The 'farel-bench' project is a benchmark tool for testing LLM reasoning abilities with family relationship quizzes. It generates quizzes based on family relationships of varying degrees and measures the accuracy of large language models in solving these quizzes. The project provides scripts for generating quizzes, running models locally or via APIs, and calculating benchmark metrics. The quizzes are designed to test logical reasoning skills using family relationship concepts, with the goal of evaluating the performance of language models in this specific domain.

NNtrainer is a software framework for training neural network models on devices with limited resources. It enables on-device fine-tuning of neural networks using user data for personalization. NNtrainer supports various machine learning algorithms and provides examples for tasks such as few-shot learning, ResNet, VGG, and product rating. It is optimized for embedded devices and utilizes CBLAS and CUBLAS for accelerated calculations. NNtrainer is open source and released under the Apache License version 2.0.

This repository compiles a list of academic papers that evaluate, align, simulate, and provide surveys or perspectives on the use of Large Language Models (LLMs) in the field of Social Science. The papers cover various aspects of LLM research, including assessing their alignment with human values, evaluating their capabilities in tasks such as opinion formation and moral reasoning, and exploring their potential for simulating social interactions and addressing issues in diverse fields of Social Science. The repository aims to provide a comprehensive resource for researchers and practitioners interested in the intersection of LLMs and Social Science.

AutoPatent is a multi-agent framework designed for automatic patent generation. It challenges large language models to generate full-length patents based on initial drafts. The framework leverages planner, writer, and examiner agents along with PGTree and RRAG to craft lengthy, intricate, and high-quality patent documents. It introduces a new metric, IRR (Inverse Repetition Rate), to measure sentence repetition within patents. The tool aims to streamline the patent generation process by automating the creation of detailed and specialized patent documents.

A curated collection of papers and resources on Mixture of Experts in Large Language Models. The repository provides a chronological overview of several representative Mixture-of-Experts (MoE) models in recent years, structured according to release dates. It covers MoE models from various domains like Natural Language Processing (NLP), Computer Vision, Multimodal, and Recommender Systems. The repository aims to offer insights into Inference Optimization Techniques, Sparsity exploration, Attention mechanisms, and safety enhancements in MoE models.

Quantus is a toolkit designed for the evaluation of neural network explanations. It offers more than 30 metrics in 6 categories for eXplainable Artificial Intelligence (XAI) evaluation. The toolkit supports different data types (image, time-series, tabular, NLP) and models (PyTorch, TensorFlow). It provides built-in support for explanation methods like captum, tf-explain, and zennit. Quantus is under active development and aims to provide a comprehensive set of quantitative evaluation metrics for XAI methods.

Kafka-ML is a framework designed to manage the pipeline of Tensorflow/Keras and PyTorch machine learning models on Kubernetes. It enables the design, training, and inference of ML models with datasets fed through Apache Kafka, connecting them directly to data streams like those from IoT devices. The Web UI allows easy definition of ML models without external libraries, catering to both experts and non-experts in ML/AI.

Java & Python programming assistant for AI model inference.

Expert in applying mental models across various domains.

Discover A More Robust Business: Craft tailored value proposition statements, develop a comprehensive business model canvas, conduct detailed PESTLE analysis, and gain strategic insights on enhancing business model elements like scalability, cost structure, and market competition strategies. (v1.18)

A software architect for C4 Model generation.

Let's get started by telling me about your business: What do you offer? Who do you serve? ------------------------------------------------------- Need help Prompt Engineering? Reach out on LinkedIn: StephenHnilica

Business Model Canvas Creator - Build and evaluate your business model

Discover if your group, relationship or organization uses specific methods to recruit and maintain control over people

Generates Environmental impact assessment templates based on specific global locations and parameters.

Expert in Marian NMT models and training

Un aiuto a costruire il Business Model Canvas della tua iniziativa

Expert in ML model optimization and tuning!

Business model expert, create detailed reports based on business ideas.

是一个专门用于建立数学模型并撰写python代码的gpt.

Assists with ROMS and COAWST modeling in Linux environments.

Consultor experto en Business Model Canvas para emprendedores

Expert on AI Model NFT Marketplace, offering insights on blockchain tech and NFTs.

Expertly Crafting Your GPT From Concept to Masterpiece

Super Prompter is an AI model designed to create high-quality prompts for chatbots. It thinks like a human in crafting prompts, leveraging various methods like the role method, knowledge level method, and emotion method. This AI model has the capability to generate prompts for any given scenario

Model Vibe Picture Creator: Unleash Your Imagination! 🎨📸 Generates detailed, cool prompts for stylized images, perfect for AI tools like DALL-E 3. 🔥👾