Best AI tools for< Build Encoders >

Build Club is a leading training campus for AI learners, experts, and builders. It offers a platform where individuals can upskill into AI careers, get certified by top AI companies, learn the latest AI tools, and earn money by solving real problems. The community at Build Club consists of AI learners, engineers, consultants, and founders who collaborate on cutting-edge AI projects. The platform provides challenges, support, and resources to help individuals build AI projects and advance their skills in the field.

This is a unified DevOps platform to build AI applications. It provides a comprehensive set of tools and services to help developers build, deploy, and manage AI applications. The platform includes a variety of features such as a code editor, a debugger, a profiler, and a deployment manager. It also provides access to a variety of AI services, such as natural language processing, machine learning, and computer vision.

Build Chatbot is a no-code chatbot builder designed to simplify the process of creating chatbots. It enables users to build their chatbot without any coding knowledge, auto-train it with personalized content, and get the chatbot ready with an engaging UI. The platform offers various features to enhance user engagement, provide personalized responses, and streamline communication with website visitors. Build Chatbot aims to save time for both businesses and customers by making information easily accessible and transforming visitors into satisfied customers.

Build Club is an AI tool designed to help individuals learn and explore various aspects of artificial intelligence. The platform offers a wide range of courses, challenges, hackathons, and community projects to enhance users' AI skills. Users can build AI models for tasks like image and video generation, AI marketing, and creating AI agents. Build Club aims to create a collaborative learning environment for AI enthusiasts to grow their knowledge and skills in the field of artificial intelligence.

The website 'What should I build next?' is a platform designed to help developers generate random development project ideas. It serves as the ultimate resource for developers seeking inspiration for their next project. Users can pick components or randomize to generate unique project ideas. The platform also offers a Challenge Mode for added excitement. Additionally, free credits are rewarded to active users daily, ensuring a continuous flow of ideas. The website aims to support developers in overcoming creative blocks and sparking innovation.

GitHub is a collaborative platform for building and shipping software that offers various features such as GitHub Copilot for AI-powered coding assistance, security tools for finding and fixing vulnerabilities, automation of workflows, instant development environments, project management, code review, and collaboration tools. It aims to simplify the software development process and improve developer productivity by leveraging AI technology.

Google Cloud is a suite of cloud computing services that runs on the same infrastructure as Google. Its services include computing, storage, networking, databases, machine learning, and more. Google Cloud is designed to make it easy for businesses to develop and deploy applications in the cloud. It offers a variety of tools and services to help businesses with everything from building and deploying applications to managing their infrastructure. Google Cloud is also committed to sustainability, and it has a number of programs in place to reduce its environmental impact.

Airtable is a next-gen app-building platform that enables teams to create custom business apps without the need for coding. It offers features like AI integration, connected data, automations, interface design, and data visualization. Airtable allows users to manage security, permissions, and data protection at scale. The platform also provides integrations with popular tools like Slack, Google Drive, and Salesforce, along with an extension marketplace for additional templates and apps. Users can streamline workflows, automate processes, and gain insights through reporting and analytics.

Cloudflare is a platform that offers a range of products and services to help users build, secure, and optimize their websites and applications. It provides solutions for web analytics, troubleshooting errors, domain registration, content delivery, and more. Cloudflare also offers developer products like Workers and AI products like AI Vectorize and AI Gateway. Additionally, Cloudflare provides Zero Trust Access, Tunnel Gateway, and Browser Isolation services to enhance security and performance. The platform aims to simplify the process of managing online assets and improving user experience.

Gemini is a large and powerful AI model developed by Google. It is designed to handle a wide variety of text and image reasoning tasks, and it can be used to build a variety of AI-powered applications. Gemini is available in three sizes: Ultra, Pro, and Nano. Ultra is the most capable model, but it is also the most expensive. Pro is the best performing model for a wide variety of tasks, and it is a good value for the price. Nano is the most efficient model, and it is designed for on-device use cases.

Notion is an AI-integrated workspace platform that combines wiki, docs, and project management functionalities in one tool. It offers a centralized hub for teams to collaborate, share knowledge, manage projects, and streamline workflows. With AI assistance, users can enhance their productivity by automating tasks, generating content, and finding information quickly. Notion aims to simplify work processes and empower teams to work more efficiently and creatively.

FlutterFlow is a low-code development platform that enables users to build cross-platform mobile and web applications without writing code. It provides a visual interface for designing user interfaces, connecting data, and implementing complex logic. FlutterFlow is trusted by users at leading companies around the world and has been used to build a wide range of applications, from simple prototypes to complex enterprise solutions.

Enhancv is an AI-powered online resume builder that helps users create professional resumes and cover letters tailored to their job applications. The tool offers a drag-and-drop resume builder with a variety of modern templates, a resume checker that evaluates resumes for ATS-friendliness, and provides actionable suggestions. Enhancv also provides resume and CV examples written by experienced professionals, a resume tailoring feature, and a free resume checker. Users can download their resumes in PDF or TXT formats and store up to 30 documents in cloud storage.

Bubble is a no-code application development platform that allows users to build and deploy web and mobile applications without writing any code. It provides a visual interface for designing and developing applications, and it includes a library of pre-built components and templates that can be used to accelerate development. Bubble is suitable for a wide range of users, from beginners with no coding experience to experienced developers who want to build applications quickly and easily.

Zyro is a website builder that allows users to create professional websites and online stores without any coding knowledge. It offers a range of features, including customizable templates, drag-and-drop editing, and AI-powered tools to help users brand and grow their businesses.

Abacus.AI is the world's first AI platform where AI, not humans, build Applied AI agents and systems at scale. Using generative AI and other novel neural net techniques, AI can build LLM apps, gen AI agents, and predictive applied AI systems at scale.

Pinecone is a vector database that helps power AI for the world's best companies. It is a serverless database that lets you deliver remarkable GenAI applications faster, at up to 50x lower cost. Pinecone is easy to use and can be integrated with your favorite cloud provider, data sources, models, frameworks, and more.

Cursor is an AI-first code editor that helps developers build software faster. It provides a variety of features to help developers, including code completion, code generation, and error detection. Cursor is also designed to be easy to use and integrates with popular development tools like VSCode.

Weaviate is an AI-native database that empowers developers to build and scale modern AI applications more easily. It offers cloud, model, and deployment agnostic solutions, flexible cost-performance optimization, and a robust developer community. With lightning-fast pure vector similarity search capabilities, integrations with various language model frameworks, and a focus on security, Weaviate is a versatile tool for AI development.

GPT Engineer is an AI tool designed to help users build web applications 10x faster by chatting with AI. Users can sync their projects with GitHub and deploy them with a single click. The tool offers features like displaying top stories from Hacker News, creating landing pages for startups, tracking crypto portfolios, managing startup operations, and building front-end with React, Tailwind & Vite. GPT Engineer is currently in beta and aims to streamline the web development process for users.

ModernBERT is a repository focused on modernizing BERT through architecture changes and scaling. It introduces FlexBERT, a modular approach to encoder building blocks, and heavily relies on .yaml configuration files to build models. The codebase builds upon MosaicBERT and incorporates Flash Attention 2. The repository is used for pre-training and GLUE evaluations, with a focus on reproducibility and documentation. It provides a collaboration between Answer.AI, LightOn, and friends.

Superlinked is a compute framework for information retrieval and feature engineering systems, focusing on converting complex data into vector embeddings for RAG, Search, RecSys, and Analytics stack integration. It enables custom model performance in machine learning with pre-trained model convenience. The tool allows users to build multimodal vectors, define weights at query time, and avoid postprocessing & rerank requirements. Users can explore the computational model through simple scripts and python notebooks, with a future release planned for production usage with built-in data infra and vector database integrations.

fastRAG is a research framework designed to build and explore efficient retrieval-augmented generative models. It incorporates state-of-the-art Large Language Models (LLMs) and Information Retrieval to empower researchers and developers with a comprehensive tool-set for advancing retrieval augmented generation. The framework is optimized for Intel hardware, customizable, and includes key features such as optimized RAG pipelines, efficient components, and RAG-efficient components like ColBERT and Fusion-in-Decoder (FiD). fastRAG supports various unique components and backends for running LLMs, making it a versatile tool for research and development in the field of retrieval-augmented generation.

LLM2Vec is a simple recipe to convert decoder-only LLMs into text encoders. It consists of 3 simple steps: 1) enabling bidirectional attention, 2) training with masked next token prediction, and 3) unsupervised contrastive learning. The model can be further fine-tuned to achieve state-of-the-art performance.

Langroid is a Python framework that makes it easy to build LLM-powered applications. It uses a multi-agent paradigm inspired by the Actor Framework, where you set up Agents, equip them with optional components (LLM, vector-store and tools/functions), assign them tasks, and have them collaboratively solve a problem by exchanging messages. Langroid is a fresh take on LLM app-development, where considerable thought has gone into simplifying the developer experience; it does not use Langchain.

Curated Transformers is a transformer library for PyTorch that provides state-of-the-art models composed of reusable components. It supports various transformer architectures, including encoders like ALBERT, BERT, and RoBERTa, and decoders like Falcon, Llama, and MPT. The library emphasizes consistent type annotations, minimal dependencies, and ease of use for education and research. It has been production-tested by Explosion and will be the default transformer implementation in spaCy 3.7.

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.

Eagle is a family of Vision-Centric High-Resolution Multimodal LLMs that enhance multimodal LLM perception using a mix of vision encoders and various input resolutions. The model features a channel-concatenation-based fusion for vision experts with different architectures and knowledge, supporting up to over 1K input resolution. It excels in resolution-sensitive tasks like optical character recognition and document understanding.

A collection of LLM services you can self host via docker or modal labs to support your applications development. The goal is to provide docker containers or modal labs deployments of common patterns when using LLMs and endpoints to integrate easily with existing codebases using the openai api. It supports GPT4all's embedding api, JSONFormer api for chat completion, Cross Encoders based on sentence transformers, and provides documentation using MkDocs.

RAG Me Up is a generic framework that enables users to perform Retrieve and Generate (RAG) on their own dataset easily. It consists of a small server and UIs for communication. Best run on GPU with 16GB vRAM. Users can combine RAG with fine-tuning using LLaMa2Lang repository. The tool allows configuration for LLM, data, LLM parameters, prompt, and document splitting. Funding is sought to democratize AI and advance its applications.

RAG Me Up is a generic framework that enables users to perform Retrieve, Answer, Generate (RAG) on their own dataset easily. It consists of a small server and UIs for communication. The tool can run on CPU but is optimized for GPUs with at least 16GB of vRAM. Users can combine RAG with fine-tuning using the LLaMa2Lang repository. The tool provides a configurable RAG pipeline without the need for coding, utilizing indexing and inference steps to accurately answer user queries.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for popular models like FlagEmbedding, Ember, GTE, and E5. It implements features such as no model graph compilation step, Metal support for local execution on Macs, small docker images with fast boot times, token-based dynamic batching, optimized transformers code for inference using Flash Attention, Candle, and cuBLASLt, Safetensors weight loading, and production-ready features like distributed tracing with Open Telemetry and Prometheus metrics.

This repository contains a collection of papers and resources related to Large Language Models (LLMs), including their applications in various domains such as text generation, translation, question answering, and dialogue systems. The repository also includes discussions on the ethical and societal implications of LLMs. **Description** This repository is a collection of papers and resources related to Large Language Models (LLMs). LLMs are a type of artificial intelligence (AI) that can understand and generate human-like text. They have a wide range of applications, including text generation, translation, question answering, and dialogue systems. **For Jobs** - **Content Writer** - **Copywriter** - **Editor** - **Journalist** - **Marketer** **AI Keywords** - **Large Language Models** - **Natural Language Processing** - **Machine Learning** - **Artificial Intelligence** - **Deep Learning** **For Tasks** - **Generate text** - **Translate text** - **Answer questions** - **Engage in dialogue** - **Summarize text**

Lean Copilot is a tool that enables the use of large language models (LLMs) in Lean for proof automation. It provides features such as suggesting tactics/premises, searching for proofs, and running inference of LLMs. Users can utilize built-in models from LeanDojo or bring their own models to run locally or on the cloud. The tool supports platforms like Linux, macOS, and Windows WSL, with optional CUDA and cuDNN for GPU acceleration. Advanced users can customize behavior using Tactic APIs and Model APIs. Lean Copilot also allows users to bring their own models through ExternalGenerator or ExternalEncoder. The tool comes with caveats such as occasional crashes and issues with premise selection and proof search. Users can get in touch through GitHub Discussions for questions, bug reports, feature requests, and suggestions. The tool is designed to enhance theorem proving in Lean using LLMs.

runpod-worker-comfy is a serverless API tool that allows users to run any ComfyUI workflow to generate an image. Users can provide input images as base64-encoded strings, and the generated image can be returned as a base64-encoded string or uploaded to AWS S3. The tool is built on Ubuntu + NVIDIA CUDA and provides features like built-in checkpoints and VAE models. Users can configure environment variables to upload images to AWS S3 and interact with the RunPod API to generate images. The tool also supports local testing and deployment to Docker hub using Github Actions.

Awesome-LLM-Large-Language-Models-Notes is a repository that provides a comprehensive collection of information on various Large Language Models (LLMs) classified by year, size, and name. It includes details on known LLM models, their papers, implementations, and specific characteristics. The repository also covers LLM models classified by architecture, must-read papers, blog articles, tutorials, and implementations from scratch. It serves as a valuable resource for individuals interested in understanding and working with LLMs in the field of Natural Language Processing (NLP).

This repository is a collection of papers focused on understanding the internal mechanism of large language models (LLM). It includes research on topics such as how LLMs handle multilingualism, learn in-context, and handle factual associations. The repository aims to provide insights into the inner workings of transformer-based language models through a curated list of papers and surveys.

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街を作ろう　街を作ろう　変わらぬ鼓動　弾ませろよ (作者: @_saip_)

Guides to Build a Successful Network State

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Helps you build an OpenAI Assistant Client

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Business Model Canvas Creator - Build and evaluate your business model

Build your own League of Legends Style Champion with Abilities, Back Story and Splash Art

Your tech buddy helping you refurbish or build a PC from scratch, tailored to your needs, budget, and language.

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This GPT will build app & answer questions for flipper zero.

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Build on the XRP Ledger with assistance from this GPT trained on extensive documentation and code samples.

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