Best AI tools for< Align Images >

Imagen is an AI application that leverages text-to-image diffusion models to create photorealistic images based on input text. The application utilizes large transformer language models for text understanding and diffusion models for high-fidelity image generation. Imagen has achieved state-of-the-art results in terms of image fidelity and alignment with text. The application is part of Google Research's text-to-image work and focuses on encoding text for image synthesis effectively.

Crusoe is a cloud computing platform that offers scalable, climate-aligned digital infrastructure optimized for high-performance computing and artificial intelligence. It provides cost-effective solutions by utilizing wasted, stranded, or clean energy sources to power computing resources. The platform supports AI workloads, computational biology, graphics rendering, and more, while reducing greenhouse gas emissions and maximizing resource efficiency.

StockPhotoAI.net is an AI-powered platform that allows users to generate unique and personalized stock photos for slideshows, websites, or print media. By leveraging advanced AI technology, users can create high-quality images that perfectly align with their branding and target audience. The platform offers a user-friendly experience, enabling individuals to easily describe the desired photo in plain English and receive professional photos generated by the latest OpenAI Dall-E models. With StockPhotoAI.net, users can save time and effort by avoiding the hassle of browsing through generic stock photos and instead access a wide range of realistic and professional-looking images tailored to their specific needs.

aoGen is an AI tool that focuses on generating AI fashion models and high-quality images at fractional costs. It offers an all-in-one ecommerce creative solution for showcasing clothing with a variety of models that align with brand aesthetics. Users can easily create AI fashion models in bulk using features like AI Model Upscale, Hands Repair, Repaint, and Eraser Pen. The platform also provides outstanding examples and resources through its blog and help center. Join aoGen's Discord community and visit their YouTube channel to exchange user experiences and unlock your imagination.

ContentPie is an AI-powered content creation platform designed to help users drive organic traffic and improve search engine rankings. It offers automatic SEO-optimized content generation, personalized content creation, and custom on-brand AI images. With features like generating articles in bulk, managing content with ease, and creating visuals that align with the article's theme, ContentPie aims to provide a comprehensive solution for content creation and SEO optimization. Users can also publish content to their website with just one click, collaborate with editors, and receive 24/7 support through a dedicated Slack channel.

MyQRCode.com™ is an advanced QR code generator that empowers businesses and individuals to create, customize, and track QR codes for various purposes. With its user-friendly interface and powerful features, MyQRCode.com™ simplifies the process of generating QR codes, making it accessible to anyone. The platform offers a wide range of QR code types, including website URLs, vCards, PDFs, images, social media profiles, videos, simple text, business pages, Facebook pages, Wi-Fi networks, and app downloads. MyQRCode.com™ also provides advanced customization options, allowing users to add their company logos, change colors, and select from a variety of designs to create visually appealing QR codes that align with their brand identity. Additionally, the platform offers comprehensive analytics, enabling users to track the performance of their QR codes, including the number of scans, scan locations, and the devices used to scan the codes. This data provides valuable insights into the effectiveness of QR code campaigns and helps businesses optimize their marketing strategies.

Noodle4 is an AI-powered platform designed for content review of User-Generated Content (UGC) and Influencer content. It offers advanced AI models that streamline manual content review processes with speed and accuracy. Noodle4 helps users to ensure that their content aligns with brand guidelines, briefs, ad compliance, and product classification. The platform allows for cross-referencing of audio, video, text, and images, making content review efficient and precise. Noodle4 also facilitates collaboration between clients and creators, providing a seamless review experience.

StyleSphere is a digital wardrobe stylist that uses AI to help you explore your wardrobe and suggest outfits that align with your personal taste and style preferences. With just a simple photo of your clothing items, you can access tailored advice that aligns with your chosen aesthetic. StyleSphere specializes in guiding men in their 30s and beyond, introducing them to the world of classic, enduring fashion. The platform focuses on quality, choosing pieces that offer an air of sophistication and elegance without saying a word. It's about building a collection that withstands the ebbs and flows of trends, pieces that are not just worn, but lived in and loved.

VMEG is an AI-powered platform that enables users to create infinite AI-crafted videos for marketing purposes. It allows users to transform their inventory and ideas into dynamic and diverse short videos instantly. The platform supports multiple input formats such as video, image, text, and URL, and utilizes AI crafting to generate high-quality videos with various effects. VMEG offers features like automatic video subtitle generation, eye-catching title creation, precise alignment of audio and vision, and easy distribution to multiple platforms. With VMEG, users can efficiently create professional-level video content and significantly improve their marketing efforts.

MyRoomDesigner.AI is the Nr.1 AI Mood Board Designer that allows users to create stunning mood boards in seconds. The AI-powered Moodboard Maker simplifies the process by enabling users to choose their style and letting the smart technology craft beautiful, professional mood boards tailored to their preferences. With a focus on interior design, fashion, and restaurant branding, the application helps users turn their ideas into visually appealing mood boards effortlessly. Users can start by selecting their creative focus, choosing design aesthetics, adding extra customization, receiving image recommendations, fine-tuning their AI design, and getting product suggestions that align with their mood board's style and theme. MyRoomDesigner.AI aims to eliminate design stress and spark creativity in users' projects.

Korl is a cloud-based product management tool that helps teams create and share product roadmaps, presentations, and updates. It integrates with tools like Jira, Google Drive, and Figma to sync data and auto-generate content. Korl uses AI to analyze project data and generate tailored presentations for different audiences, such as customers, executives, and stakeholders. It also provides real-time updates and allows for collaboration among team members.

Whimsical is an iterative workspace designed for product teams to collaborate effectively. It offers a range of tools such as flowcharts, wireframes, mind maps, and documentation features to help teams visualize ideas, streamline processes, and create a shared understanding. With Whimsical, users can generate diagrams quickly, brainstorm and organize ideas visually, and build wireframes with ease. The platform promotes clarity, collaboration, and efficiency in product development projects.

CustomerIQ is an AI platform that automatically discovers and quantifies themes across customer feedback channels like calls, surveys, tickets, and transcripts. It aggregates customer feedback, extracts and categorizes feature requests, pain points, preferences, and highlights related to customers. The platform helps align teams, prioritize work, and build a customer-obsessed culture. CustomerIQ accelerates development by scoping project requirements faster and providing actionable insights backed with context.

The AI in Business Podcast is a platform designed for non-technical business leaders seeking AI opportunities, aligning AI capabilities with strategy, and achieving ROI. The podcast features interviews with top AI executives from Fortune 500 firms and unicorn startups, exploring trends, use-cases, and best practices for practical AI adoption.

The Human-Centred Artificial Intelligence Lab (Holzinger Group) is a research group focused on developing AI solutions that are explainable, trustworthy, and aligned with human values, ethical principles, and legal requirements. The lab works on projects related to machine learning, digital pathology, interactive machine learning, and more. Their mission is to combine human and computer intelligence to address pressing problems in various domains such as forestry, health informatics, and cyber-physical systems. The lab emphasizes the importance of explainable AI, human-in-the-loop interactions, and the synergy between human and machine intelligence.

Lattice is an AI-powered people platform designed to help companies achieve operational excellence by transforming company leaders and HR teams into stewards of high performance, data-driven decision making, and meaningful work for every employee. It offers features such as team analytics, 1:1 meetings with auto-suggested agendas, engagement surveys, OKRs & goals tracking, and AI-enhancements. Lattice simplifies HR operations, reduces administrative time, and enables better data-driven decisions based on real-time insights on workforce performance and engagement.

QRCode AI is an online generator of unique and artistic AI-powered QR codes. It offers a wide range of features, including over 100 design templates, improved scan rates, rapid generation, customizable themes, and seamless integrations. QRCode AI's use cases span various industries, including brand promotion, digital ad campaigns, event invitations, product packaging, business cards, online advertising, museum exhibits, webinars, e-commerce, educational resources, music album covers, travel and tourism, corporate events, customer reviews, restaurant menus, and link trees.

AI QR Codes is an online generator that allows users to create artistic and customizable QR codes using AI technology. With a simple prompt, users can generate unique QR codes that reflect their brand or personal style. These QR codes can be used for various purposes, including marketing campaigns, digital content access, and social media connections.

CustomerIQ is an AI platform designed to drive revenue and retention by automating administrative tasks and extracting actionable insights for sales teams, customer success, marketing, and product departments. It seamlessly integrates with CRM, help desk, and messaging apps to capture and sync CRM fields, automate research, meeting briefs, and handoffs, and quantify insights for product, marketing, and customer experience. CustomerIQ prioritizes enterprise-grade security and scalability, ensuring data privacy and encryption. The platform aims to empower teams with automation and insights, allowing them to focus on building rapport while the AI handles the rest.

FinanceRants is an AI-powered financial companion that helps individuals understand their financial personality and make informed decisions to achieve financial well-being. By analyzing users' spending, saving, and investing habits, the platform provides personalized insights and actionable strategies to empower users in managing their money and mindset. With a focus on combating financial stress and promoting financial stability, FinanceRants aims to break the cycle of living paycheck to paycheck and guide users towards a more secure financial future.

LongLLaVA is a tool for scaling multi-modal LLMs to 1000 images efficiently via hybrid architecture. It includes stages for single-image alignment, instruction-tuning, and multi-image instruction-tuning, with evaluation through a command line interface and model inference. The tool aims to achieve GPT-4V level capabilities and beyond, providing reproducibility of results and benchmarks for efficiency and performance.

LitData is a tool designed for blazingly fast, distributed streaming of training data from any cloud storage. It allows users to transform and optimize data in cloud storage environments efficiently and intuitively, supporting various data types like images, text, video, audio, geo-spatial, and multimodal data. LitData integrates smoothly with frameworks such as LitGPT and PyTorch, enabling seamless streaming of data to multiple machines. Key features include multi-GPU/multi-node support, easy data mixing, pause & resume functionality, support for profiling, memory footprint reduction, cache size configuration, and on-prem optimizations. The tool also provides benchmarks for measuring streaming speed and conversion efficiency, along with runnable templates for different data types. LitData enables infinite cloud data processing by utilizing the Lightning.ai platform to scale data processing with optimized machines.

CLIPPyX is a powerful system-wide image search and management tool that offers versatile search options to find images based on their content, text, and visual similarity. With advanced features, users can effortlessly locate desired images across their entire computer's disk(s), regardless of their location or file names. The tool utilizes OpenAI's CLIP for image embeddings and text-based search, along with OCR for extracting text from images. It also employs Voidtools Everything SDK to list paths of all images on the system. CLIPPyX server receives search queries and queries collections of image embeddings and text embeddings to return relevant images.

LLM Blueprint is an official implementation of a paper that enables text-to-image generation with complex and detailed prompts. It leverages Large Language Models (LLMs) to extract critical components from text prompts, including bounding box coordinates for foreground objects, detailed textual descriptions for individual objects, and a succinct background context. The tool operates in two phases: Global Scene Generation creates an initial scene using object layouts and background context, and an Iterative Refinement Scheme refines box-level content to align with textual descriptions, ensuring consistency and improving recall compared to baseline diffusion models.

This repository contains the official implementation of RPG, a powerful training-free paradigm for text-to-image generation and editing. RPG utilizes proprietary or open-source MLLMs as prompt recaptioner and region planner with complementary regional diffusion. It achieves state-of-the-art results and can generate high-resolution images. The codebase supports diffusers and various diffusion backbones, including SDXL and SD v1.4/1.5. Users can reproduce results with GPT-4, Gemini-Pro, or local MLLMs like miniGPT-4. The repository provides tools for quick start, regional diffusion with GPT-4, and regional diffusion with local LLMs.

LLM Vision is a Home Assistant integration that allows users to analyze images, videos, and camera feeds using multimodal LLMs. It supports providers such as OpenAI, Anthropic, Google Gemini, LocalAI, and Ollama. Users can input images and videos from camera entities or local files, with the option to downscale images for faster processing. The tool provides detailed instructions on setting up LLM Vision and each supported provider, along with usage examples and service call parameters.

LLMGA (Multimodal Large Language Model-based Generation Assistant) is a tool that leverages Large Language Models (LLMs) to assist users in image generation and editing. It provides detailed language generation prompts for precise control over Stable Diffusion (SD), resulting in more intricate and precise content in generated images. The tool curates a dataset for prompt refinement, similar image generation, inpainting & outpainting, and visual question answering. It offers a two-stage training scheme to optimize SD alignment and a reference-based restoration network to alleviate texture, brightness, and contrast disparities in image editing. LLMGA shows promising generative capabilities and enables wider applications in an interactive manner.

Towhee is a cutting-edge framework designed to streamline the processing of unstructured data through the use of Large Language Model (LLM) based pipeline orchestration. It can extract insights from diverse data types like text, images, audio, and video files using generative AI and deep learning models. Towhee offers rich operators, prebuilt ETL pipelines, and a high-performance backend for efficient data processing. With a Pythonic API, users can build custom data processing pipelines easily. Towhee is suitable for tasks like sentence embedding, image embedding, video deduplication, question answering with documents, and cross-modal retrieval based on CLIP.

Translate texts in manga/images. Some manga/images will never be translated, therefore this project is born. * Image/Manga Translator * Samples * Online Demo * Disclaimer * Installation * Pip/venv * Poetry * Additional instructions for **Windows** * Docker * Hosting the web server * Using as CLI * Setting Translation Secrets * Using with Nvidia GPU * Building locally * Usage * Batch mode (default) * Demo mode * Web Mode * Api Mode * Related Projects * Docs * Recommended Modules * Tips to improve translation quality * Options * Language Code Reference * Translators Reference * GPT Config Reference * Using Gimp for rendering * Api Documentation * Synchronous mode * Asynchronous mode * Manual translation * Next steps * Support Us * Thanks To All Our Contributors :

This tool is a fork of the 3D Gaussian Splatting code. It allows users to create a dataset ready to be trained with the Gaussian Splatting code. The dataset can be used for various experiments, such as creating orthogonal images, steganography, and lenticular effects. The tool also includes a visualizer that allows users to visualize the "painting" process during the Gaussian Splatting optimization.

LafTools is a privacy-first, self-hosted, fully open source toolbox designed for programmers. It offers a wide range of tools, including code generation, translation, encryption, compression, data analysis, and more. LafTools is highly integrated with a productive UI and supports full GPT-alike functionality. It is available as Docker images and portable edition, with desktop edition support planned for the future.

ChatGPT-On-CS is an intelligent chatbot tool based on large models, supporting various platforms like WeChat, Taobao, Bilibili, Douyin, Weibo, and more. It can handle text, voice, and image inputs, access external resources through plugins, and customize enterprise AI applications based on proprietary knowledge bases. Users can set custom replies, utilize ChatGPT interface for intelligent responses, send images and binary files, and create personalized chatbots using knowledge base files. The tool also features platform-specific plugin systems for accessing external resources and supports enterprise AI applications customization.

This Helm chart bootstraps an Airflow deployment on a Kubernetes cluster using the Helm package manager. The version of this chart does not correlate to any other component. Users should not expect feature parity between OSS airflow chart and the Astronomer airflow-chart for identical version numbers. To install this helm chart remotely (using helm 3) kubectl create namespace airflow helm repo add astronomer https://helm.astronomer.io helm install airflow --namespace airflow astronomer/airflow To install this repository from source sh kubectl create namespace airflow helm install --namespace airflow . Prerequisites: Kubernetes 1.12+ Helm 3.6+ PV provisioner support in the underlying infrastructure Installing the Chart: sh helm install --name my-release . The command deploys Airflow on the Kubernetes cluster in the default configuration. The Parameters section lists the parameters that can be configured during installation. Upgrading the Chart: First, look at the updating documentation to identify any backwards-incompatible changes. To upgrade the chart with the release name `my-release`: sh helm upgrade --name my-release . Uninstalling the Chart: To uninstall/delete the `my-release` deployment: sh helm delete my-release The command removes all the Kubernetes components associated with the chart and deletes the release. Updating DAGs: Bake DAGs in Docker image The recommended way to update your DAGs with this chart is to build a new docker image with the latest code (`docker build -t my-company/airflow:8a0da78 .`), push it to an accessible registry (`docker push my-company/airflow:8a0da78`), then update the Airflow pods with that image: sh helm upgrade my-release . --set images.airflow.repository=my-company/airflow --set images.airflow.tag=8a0da78 Docker Images: The Airflow image that are referenced as the default values in this chart are generated from this repository: https://github.com/astronomer/ap-airflow. Other non-airflow images used in this chart are generated from this repository: https://github.com/astronomer/ap-vendor. Parameters: The complete list of parameters supported by the community chart can be found on the Parameteres Reference page, and can be set under the `airflow` key in this chart. The following tables lists the configurable parameters of the Astronomer chart and their default values. | Parameter | Description | Default | | :----------------------------- | :-------------------------------------------------------------------------------------------------------- | :---------------------------- | | `ingress.enabled` | Enable Kubernetes Ingress support | `false` | | `ingress.acme` | Add acme annotations to Ingress object | `false` | | `ingress.tlsSecretName` | Name of secret that contains a TLS secret | `~` | | `ingress.webserverAnnotations` | Annotations added to Webserver Ingress object | `{}` | | `ingress.flowerAnnotations` | Annotations added to Flower Ingress object | `{}` | | `ingress.baseDomain` | Base domain for VHOSTs | `~` | | `ingress.auth.enabled` | Enable auth with Astronomer Platform | `true` | | `extraObjects` | Extra K8s Objects to deploy (these are passed through `tpl`). More about Extra Objects. | `[]` | | `sccEnabled` | Enable security context constraints required for OpenShift | `false` | | `authSidecar.enabled` | Enable authSidecar | `false` | | `authSidecar.repository` | The image for the auth sidecar proxy | `nginxinc/nginx-unprivileged` | | `authSidecar.tag` | The image tag for the auth sidecar proxy | `stable` | | `authSidecar.pullPolicy` | The K8s pullPolicy for the the auth sidecar proxy image | `IfNotPresent` | | `authSidecar.port` | The port the auth sidecar exposes | `8084` | | `gitSyncRelay.enabled` | Enables git sync relay feature. | `False` | | `gitSyncRelay.repo.url` | Upstream URL to the git repo to clone. | `~` | | `gitSyncRelay.repo.branch` | Branch of the upstream git repo to checkout. | `main` | | `gitSyncRelay.repo.depth` | How many revisions to check out. Leave as default `1` except in dev where history is needed. | `1` | | `gitSyncRelay.repo.wait` | Seconds to wait before pulling from the upstream remote. | `60` | | `gitSyncRelay.repo.subPath` | Path to the dags directory within the git repository. | `~` | Specify each parameter using the `--set key=value[,key=value]` argument to `helm install`. For example, sh helm install --name my-release --set executor=CeleryExecutor --set enablePodLaunching=false . Walkthrough using kind: Install kind, and create a cluster We recommend testing with Kubernetes 1.25+, example: sh kind create cluster --image kindest/node:v1.25.11 Confirm it's up: sh kubectl cluster-info --context kind-kind Add Astronomer's Helm repo sh helm repo add astronomer https://helm.astronomer.io helm repo update Create namespace + install the chart sh kubectl create namespace airflow helm install airflow -n airflow astronomer/airflow It may take a few minutes. Confirm the pods are up: sh kubectl get pods --all-namespaces helm list -n airflow Run `kubectl port-forward svc/airflow-webserver 8080:8080 -n airflow` to port-forward the Airflow UI to http://localhost:8080/ to confirm Airflow is working. Login as _admin_ and password _admin_. Build a Docker image from your DAGs: 1. Start a project using astro-cli, which will generate a Dockerfile, and load your DAGs in. You can test locally before pushing to kind with `astro airflow start`. `sh mkdir my-airflow-project && cd my-airflow-project astro dev init` 2. Then build the image: `sh docker build -t my-dags:0.0.1 .` 3. Load the image into kind: `sh kind load docker-image my-dags:0.0.1` 4. Upgrade Helm deployment: sh helm upgrade airflow -n airflow --set images.airflow.repository=my-dags --set images.airflow.tag=0.0.1 astronomer/airflow Extra Objects: This chart can deploy extra Kubernetes objects (assuming the role used by Helm can manage them). For Astronomer Cloud and Enterprise, the role permissions can be found in the Commander role. yaml extraObjects: - apiVersion: batch/v1beta1 kind: CronJob metadata: name: "{{ .Release.Name }}-somejob" spec: schedule: "*/10 * * * *" concurrencyPolicy: Forbid jobTemplate: spec: template: spec: containers: - name: myjob image: ubuntu command: - echo args: - hello restartPolicy: OnFailure Contributing: Check out our contributing guide! License: Apache 2.0 with Commons Clause

InternLM-XComposer2 is a groundbreaking vision-language large model (VLLM) based on InternLM2-7B excelling in free-form text-image composition and comprehension. It boasts several amazing capabilities and applications: * **Free-form Interleaved Text-Image Composition** : InternLM-XComposer2 can effortlessly generate coherent and contextual articles with interleaved images following diverse inputs like outlines, detailed text requirements and reference images, enabling highly customizable content creation. * **Accurate Vision-language Problem-solving** : InternLM-XComposer2 accurately handles diverse and challenging vision-language Q&A tasks based on free-form instructions, excelling in recognition, perception, detailed captioning, visual reasoning, and more. * **Awesome performance** : InternLM-XComposer2 based on InternLM2-7B not only significantly outperforms existing open-source multimodal models in 13 benchmarks but also **matches or even surpasses GPT-4V and Gemini Pro in 6 benchmarks** We release InternLM-XComposer2 series in three versions: * **InternLM-XComposer2-4KHD-7B** 🤗: The high-resolution multi-task trained VLLM model with InternLM-7B as the initialization of the LLM for _High-resolution understanding_ , _VL benchmarks_ and _AI assistant_. * **InternLM-XComposer2-VL-7B** 🤗 : The multi-task trained VLLM model with InternLM-7B as the initialization of the LLM for _VL benchmarks_ and _AI assistant_. **It ranks as the most powerful vision-language model based on 7B-parameter level LLMs, leading across 13 benchmarks.** * **InternLM-XComposer2-VL-1.8B** 🤗 : A lightweight version of InternLM-XComposer2-VL based on InternLM-1.8B. * **InternLM-XComposer2-7B** 🤗: The further instruction tuned VLLM for _Interleaved Text-Image Composition_ with free-form inputs. Please refer to Technical Report and 4KHD Technical Reportfor more details.

Video-subtitle-remover (VSR) is a software based on AI technology that removes hard subtitles from videos. It achieves the following functions: - Lossless resolution: Remove hard subtitles from videos, generate files with subtitles removed - Fill the region of removed subtitles using a powerful AI algorithm model (non-adjacent pixel filling and mosaic removal) - Support custom subtitle positions, only remove subtitles in defined positions (input position) - Support automatic removal of all text in the entire video (no input position required) - Support batch removal of watermark text from multiple images.

This repository contains the code and instructions needed to build a sophisticated answer engine that leverages the capabilities of Groq, Mistral AI's Mixtral, Langchain.JS, Brave Search, Serper API, and OpenAI. Designed to efficiently return sources, answers, images, videos, and follow-up questions based on user queries, this project is an ideal starting point for developers interested in natural language processing and search technologies.

Gemini is an open-source model designed to handle multiple modalities such as text, audio, images, and videos. It utilizes a transformer architecture with special decoders for text and image generation. The model processes input sequences by transforming them into tokens and then decoding them to generate image outputs. Gemini differs from other models by directly feeding image embeddings into the transformer instead of using a visual transformer encoder. The model also includes a component called Codi for conditional generation. Gemini aims to effectively integrate image, audio, and video embeddings to enhance its performance.

Q-Bench is a benchmark for general-purpose foundation models on low-level vision, focusing on multi-modality LLMs performance. It includes three realms for low-level vision: perception, description, and assessment. The benchmark datasets LLVisionQA and LLDescribe are collected for perception and description tasks, with open submission-based evaluation. An abstract evaluation code is provided for assessment using public datasets. The tool can be used with the datasets API for single images and image pairs, allowing for automatic download and usage. Various tasks and evaluations are available for testing MLLMs on low-level vision tasks.

FlashRank is an ultra-lite and super-fast Python library designed to add re-ranking capabilities to existing search and retrieval pipelines. It is based on state-of-the-art Language Models (LLMs) and cross-encoders, offering support for pairwise/pointwise rerankers and listwise LLM-based rerankers. The library boasts the tiniest reranking model in the world (~4MB) and runs on CPU without the need for Torch or Transformers. FlashRank is cost-conscious, with a focus on low cost per invocation and smaller package size for efficient serverless deployments. It supports various models like ms-marco-TinyBERT, ms-marco-MiniLM, rank-T5-flan, ms-marco-MultiBERT, and more, with plans for future model additions. The tool is ideal for enhancing search precision and speed in scenarios where lightweight models with competitive performance are preferred.

EVE is an official PyTorch implementation of Unveiling Encoder-Free Vision-Language Models. The project aims to explore the removal of vision encoders from Vision-Language Models (VLMs) and transfer LLMs to encoder-free VLMs efficiently. It also focuses on bridging the performance gap between encoder-free and encoder-based VLMs. EVE offers a superior capability with arbitrary image aspect ratio, data efficiency by utilizing publicly available data for pre-training, and training efficiency with a transparent and practical strategy for developing a pure decoder-only architecture across modalities.

Transforms your portrait into unique alien avatars. Upload an image (png, jpg, or jpeg). v1.1

Align lessons to Common Core math standards

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Guides strategic workforce planning to align with organizational goals.

Align, organize, and enhance design assets effortlessly.

Helps UK firms align marketing content with the FCA's financial promotion rules and the CAP Code 📋

Rewrites resumes to align with targeted job postings.

Your go-to for understanding how current events align with generational cycles.

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Insights on Diversity, Equality, and Inclusion - This AI chat provides info on DEI topics, but opinions may not align with all views. Use responsibly, consult experts, and promote respectful discussions.

Crea situaciones de aprendizaje de acuerdo a los Currículos de Educacion Secundaria y Bachillerato de Asturias en el marco de la LOMLOE, para la especialidad, curso y temática proporcionados

Your guide to aligning lesson plans with Common Core standards. Standards checked and updated daily.

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Sharpening Business Ideas is an AI-driven tool that refines business concepts and evaluates pitches. It aligns ideas with market trends and best practices, transforming them into market-ready proposals. Perfect for entrepreneurs and innovators, Your own Shark Tank for strategic guidance

Engaging and supportive AI for strategic OKR planning.

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Guiding you from ambiguous ideas through structured and effective OKRs (Objectives and Key Results)

Creates measurable objectives from educational documents and suggests assessments based on those LO's. PDF's work best.