Showing 1873 open source projects for "no code"

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  • 1
    Generic engine to filter information. We wish to show that the power of expression of a filter makes it possible to appreciably reduce the size of the code necessary to extract information and that it is possible in Python.
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  • 2

    text_summurization_abstractive_methods

    Multiple implementations for abstractive text summurization

    This repo is built to collect multiple implementations for abstractive approaches to address text summarization it is built to simply run on google colab , in one notebook so you would only need an internet connection to run these examples without the need to have a powerful machine , so all the code examples would be in a jupyter format , and you don't have to download data to your device as we connect these jupyter notebooks to google drive
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  • 3
    Synesketch is a software library with synesthetic abilities, made for Processing digital artists. Its code serves as a medium between words, emotions, and images. Synesketch homepage: http://synesketch.krcadinac.com
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  • 4
    QOTD Lite Discord Bot

    QOTD Lite Discord Bot

    Simpler version of: Simple Question Of The Day (QOTD) Discord Bot you

    ...This bot is the Lite version of QOTD-Bot at [https://github.com/itsmarsss/QOTD-Bot]; QOTD managers can send QOTDs to a specific channel and a thread will be made for users to answer the question. How to set it up? Simply follow a tutorial to create a Discord bot and run the code. Pass in the bot's token and configure the bot through the commands in qotd help. Restrictions? The bot will only work on one server The bot must be self-hosted
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  • 5
    using simple cuboids and gjk algorithm, this general purpose algorithm gives a ready made code to work with swissranger 3D camera.
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  • 6
    It's a Cat and Dog game,we develop the Inner AI strategy for the Dog and we also code the strategy of the cat in order to simulate the user. Furthermore we use Artificial Neural Network to build the experiment
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  • 7
    QSO-Graph

    QSO-Graph

    Ham radio MCP servers for AI Agents — 71 tools, 11 packages

    ...Provides AI-powered access to QRZ, eQSL, LoTW, HamQTH, POTA, SOTA, IOTA, WSPR, solar weather, ADIF parsing, and HF Description: Propagation analytics. Native installers for Windows (InnoSetup) and Linux (RPM). All servers also available via pip from PyPI. Source code at github.com/qso-graph.
    Downloads: 0 This Week
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  • 8
    BLEURT-20-D12

    BLEURT-20-D12

    Custom BLEURT model for evaluating text similarity using PyTorch

    ...Unlike standard BLEURT models from TensorFlow, this version is built from a custom PyTorch transformer library. It requires installing the model-specific library from GitHub to function properly. Once set up, it can be used to compute similarity scores with minimal code. BLEURT-20-D12 enables more flexible deployment in PyTorch-based workflows for evaluating language generation outputs.
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  • 9
    TARILIO

    TARILIO

    Advanced Full Text Search + AI Assistant + Local Server for LLMs

    TARILIO Pro platform for Information Retrieval that can work on a LAN as both client and LLM server. Advanced features: set LLM sampler parameters, scrolling index vocabulary, multilingual stemming, synonyms. MCP Client. UI can be translated using a free Language File Translator. Uses Llama Sharp and Lucene search engine . Open source and free. TARILIO PRO commercial version.
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  • 10
    DeepSeek R1 AI

    DeepSeek R1 AI

    TN 365 DeepSeek R1 - Assistant Vocal Mutli taches IA 100% local !

    🇫🇷 TN365 AI Edition est une version avancée de TN365, conçue pour offrir une expérience Linux moderne, rapide et entièrement orientée intelligence artificielle. Cette édition intègre DeepSeek R1 3B, un modèle open‑source puissant optimisé pour le raisonnement, le code et l’analyse, permettant un assistant IA local performant sans dépendance cloud. TN365 AI propose un dock IA dédié, Terminal AI, Page Assist, un branding futuriste et une optimisation complète pour l’usage quotidien. Pensé pour les créateurs, développeurs et passionnés d’IA, TN365 AI Edition combine stabilité, élégance et puissance dans une distribution unique.
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  • 11
    kombinatoriC delta library

    kombinatoriC delta library

    CAS Algorithms embeded as libraries.

    Personal research achievements from the authors presented here in the form of symbolic Algebra and non-numerical analysis algorithms implemented in C/C++, Java, and/or Pascal. As part of a more wide, simple, powerful and robust CAS enviroment under development, new code will be continuously added up to this repository. The authors give their welcome and encouragement to everyone interested in bring some kind of collaboration.
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  • 12
    Hermes 4

    Hermes 4

    Hermes 4 FP8: hybrid reasoning Llama-3.1-405B model by Nous Research

    ...It introduces a hybrid reasoning mode with explicit <think> segments, enabling the model to deliberate deeply when needed and switch to faster responses when desired. Post-training improvements include a vastly expanded corpus with ~60B tokens, boosting performance across math, code, STEM, logic, creativity, and structured outputs. The model is designed for schema adherence, producing valid JSON and repairing malformed outputs, making it highly suitable for tool use and function calling. Hermes 4 is engineered for superior steerability with reduced refusal rates, aligning responses to user values while preserving assistant quality. ...
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  • 13
    wav2vec2-large-xlsr-53-portuguese

    wav2vec2-large-xlsr-53-portuguese

    Portuguese ASR model fine-tuned on XLSR-53 for 16kHz audio input

    wav2vec2-large-xlsr-53-portuguese is an automatic speech recognition (ASR) model fine-tuned on Portuguese using the Common Voice 6.1 dataset. It is based on Facebook’s wav2vec2-large-xlsr-53, a multilingual self-supervised learning model, and is optimized to transcribe Portuguese speech sampled at 16kHz. The model performs well without a language model, though adding one can improve word error rate (WER) and character error rate (CER). It achieves a WER of 11.3% (or 9.01% with LM) on Common...
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  • 14

    automated-linguistic-analysis

    Automated Linguistic Analysis, with both monolith and cluster versions

    Sample application showcasing usage of technologies such as: * OSGi R7 Promises for asynchronous generation of transcriptions and linguistic analyses * OSGi R7 Push Stream and JAX RS Server Sent Events for push notifications of processing status * Apache Camel 2.23.1 and RabbitMQ 3.7 for asynchronous communication between services * JPA 2.1 and Hibernate 5.2.12, along with OSGi R7 JPA and Transaction Control services, for persistence layer * OSGi R7 HTTP and JAX RS Whiteboard for registering servlets, resources and REST controllers * OSGi R7 Configurator, Configuration Admin and Metatype services for automatic configuration of components * OSGi R7 Declarative Services for dependency injection * Maven automated build of Docker images * Maven automated deployment into Kubernetes cluster * RabbitMQ message broker as a StatefulSet * CockroachDB relational database as a StatefulSet See 'Code' tab for detailed information
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  • 15
    ** IMPORTANT NOTICE ** 10 Feb 2006 Code is being moved to the SMI subversion repository (http://smi-protege.stanford.edu/svn/owl/trunk/) Project will continue to be open source. ProtegeOWL info at: http://protege.stanford.edu/overview/protege-owl.html
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  • 16
    Nex-N2-mini

    Nex-N2-mini

    Compact agentic model for coding, tools, and productivity tasks

    ...Built on Qwen3.5-35B-A3B-Base, it offers a lighter latency and deployment profile than Nex-N2-Pro while preserving the core Nex-N2 “Agentic Thinking” framework. This framework unifies requirement understanding, planning, code implementation, environmental feedback, debugging, evaluation, and iteration into a closed loop. It uses adaptive thinking to decide when deeper reasoning is needed and coherent thinking to keep reasoning consistent across tasks and modalities. Nex-N2-mini supports image-text-to-text workflows, explicit reasoning traces, robust function calling, and deployment through Transformers, vLLM, SGLang, Docker, and quantized local apps. ...
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  • 17
    GigaChat 3 Ultra

    GigaChat 3 Ultra

    High-performance MoE model with MLA, MTP, and multilingual reasoning

    ...The model also employs Multi-Token Prediction, enabling multi-step token generation in a single pass for up to 40% faster output through speculative and parallel decoding techniques. Its training corpus incorporates ten languages, enriched with books, academic sources, code datasets, mathematical tasks, and more than 5.5 trillion tokens of high-quality synthetic data. This combination significantly boosts reasoning, coding, and multilingual performance across modern benchmarks. Designed for high-performance deployment, GigaChat 3 Ultra supports major inference engines and offers optimized BF16 and FP8 execution paths for cluster-grade hardware.
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  • 18
    OpenVLA 7B

    OpenVLA 7B

    Vision-language-action model for robot control via images and text

    OpenVLA 7B is a multimodal vision-language-action model trained on 970,000 robot manipulation episodes from the Open X-Embodiment dataset. It takes camera images and natural language instructions as input and outputs normalized 7-DoF robot actions, enabling control of multiple robot types across various domains. Built on top of LLaMA-2 and DINOv2/SigLIP visual backbones, it allows both zero-shot inference for known robot setups and parameter-efficient fine-tuning for new domains. The model...
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  • 19
    Llama-3.2-1B-Instruct

    Llama-3.2-1B-Instruct

    Instruction-tuned 1.2B LLM for multilingual text generation by Meta

    Llama-3.2-1B-Instruct is Meta’s multilingual, instruction-tuned large language model with 1.24 billion parameters, optimized for dialogue, summarization, and retrieval tasks. It builds upon the Llama 3.1 architecture and incorporates fine-tuning techniques like SFT, DPO, and quantization-aware training for improved alignment, efficiency, and safety. The model supports eight primary languages (including English, Spanish, Hindi, and Thai) and was trained on a curated mix of publicly available...
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  • 20
    Qwable-v1

    Qwable-v1

    Agentic coding model combining Opus reasoning and Fable tools

    ...When configured as an agent, it can emit structured tool-use XML for file editing, shell commands, codebase navigation, and workflow automation. Qwable-v1 is designed specifically for software engineering, code editing, debugging, and autonomous coding workflows.
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  • 21
    VisitorType

    VisitorType

    Know who's really visiting: humans, AI crawlers & assistants

    VisitorType is one snippet that tells humans, AI crawlers, and AI assistants apart — verified by IP, not just the user-agent string anyone can spoof. Once you know who's really visiting, you can act on it: fire your ad pixels for humans only so you stop paying to retarget bots, serve AI crawlers structured facts about your pages, and finally see the AI referrals GA4 buries in "Direct" (the ones that convert ~4.4× organic search). It's not another dashboard that just watches your traffic —...
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  • 22
    chatbot

    chatbot

    ChatBot for WordPress WPBot Lite

    === Free AI ChatBot for WordPress - WPBot Lite Version === ChatBot for wordpress with AI for Live Chat Support & Collecting Data. NATIVE, No code, Conversational forms, ChatGPT, DialogFlow, HelpDesk = ChatBot for WordPress with AI - WPBot = ChatBot for WordPress with AI - WPBot is an easy to use, Native, No coding required, AI ChatBot for WordPress websites to provide Automated Live Chat Support. Use ChatBot to answer user questions and also collect information</strong> from the users using conversational forms for ChatBot. ...
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  • 23
    lastest

    lastest

    AI-supported visual verification and tests you can actually trust.

    Lastest.cloud is a free, open-source verification of development, self-hosted visual regression and end-to-end testing platform for web applications. An AI agent records you clicking through your running app and generates Playwright tests with multi-selector fallback. Replays are deterministic and token-free, so your CI/CD bill doesn't scale with your test suite. Lastest ships three diff engines side-by-side — pixel (pixelmatch), structural (SSIM), and perceptual (Butteraugli) — so...
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