Search Results for "no code" - Page 45
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Showing 1872 open source projects for "no code"
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minbpe
Minimal, clean code for the Byte Pair Encoding (BPE) algorithm
minbpe is a minimal, clean implementation of byte-level Byte Pair Encoding (BPE), the tokenization approach widely used in modern language models. It operates on UTF-8 encoded bytes rather than Unicode characters, which makes it robust to arbitrary text inputs and avoids needing a language-specific character vocabulary. The repository is structured as a teaching-oriented implementation that shows how to train a tokenizer by learning merge rules, then apply those merges to encode text into... -
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ollama-kit-v1.1
Portable AI stack with Ollama container, models, and Gramified GUI
...Launch the Gramified GUI as described in the README. Linux extract example: unzip ollama-kit-v1.1-full.zip Note: This release is large due to included model files. For a code-only setup (no models or container), see the main repo branch. -
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FLUX.1 Krea
Powerful open source image generation model
FLUX.1 Krea [dev] is an open-source 12-billion parameter image generation model developed collaboratively by Krea and Black Forest Labs, designed to deliver superior aesthetic control and high image quality. It is a rectified-flow model distilled from the original Krea 1, providing enhanced sampling efficiency through classifier-free guidance distillation. The model supports generation at resolutions between 1024 and 1280 pixels with recommended inference steps between 28 and 32 for optimal... -
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Grok of Death is a desktop coding assistant with GUI powered by the Grok API. Users supply their own API key — all billing is handled directly with xAI.
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Gemini of Death is a desktop coding assistant with GUI powered by the Googles Gemini API. Users supply their own API key — all billing is handled directly with Google.
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GPT of Death is a desktop coding assistant with GUI powered by the OpenAI API. Users supply their own API key — all billing is handled directly with OpenAI.
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Shinkai: Local AI Agents
Shinkai allows you to create advanced AI (local) agents effortlessly
Shinkai is a free, open-source AI platform that lets anyone create powerful AI agents without coding. These agents can collaborate with each other, handle complex tasks, and operate in decentralized crypto environments. Key Features: - No-Code Agent Creation - Build specialized agents (trading bots, sentiment trackers, etc.) with simple descriptions - Multi-Agent Collaboration - Agents work together to solve complex problems - Crypto Integration - Built-in support for decentralized payments and transactions - Flexible AI Models - Choose from cloud models (GPT-4, Claude) or run locally - Universal Compatibility - Works with Model Context Protocol (MCP) for cross-platform integration - Local Security - Crypto keys and computations stay on your device Shinkai transforms AI from single-task tools into collaborative, autonomous systems that can operate in decentralized networks while maintaining privacy and security. -
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dibnn
Drop In the Bucket Neural Networks
One more lightweight neural network in C. -
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dlric
Fork of OpenClaw at 19/march/2026 to fix bugs and enhancements
...Hope to release the first release in a few hours as soon I catchup with typescript My github account is maria901, if you can unlock it I say thanks Now back to the code -
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knoksPix
KnoksPix is an AI-first creative workspace combining different tasks.
KnoksPix is an AI-first creative workspace combining: *Intelligent image editing & adjustment workflow *Generative augmentation via Gemini / (optional) local Starcoder2 backend *Cross‑platform delivery (Web + Desktop [Electron] + Mobile [Capacitor/Android]) *Extensible architecture (pluggable model backends & tools) -
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Curated Transformers
PyTorch library of curated Transformer models and their components
State-of-the-art transformers, brick by brick. Curated Transformers is a transformer library for PyTorch. It provides state-of-the-art models that are composed of a set of reusable components. Supports state-of-the-art transformer models, including LLMs such as Falcon, Llama, and Dolly v2. Implementing a feature or bugfix benefits all models. For example, all models support 4/8-bit inference through the bitsandbytes library and each model can use the PyTorch meta device to avoid unnecessary... -
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DocWire SDK
Award-winning modern data processing SDK in C++20
DocWire SDK, a standout C++20AI driven data processing tool, has received award from SourceForge and strong backing from Microsoft. It handles nearly 100 file types, empowering efficient text extraction, web data extraction, and document analysis. For businesses, the shift to DocWire SDK signifies a leap forward. It promises comprehensive document format support and the ability to extract valuable insights from email boxes, databases, and websites using cutting-edge AI. DocWire SDK aims to... -
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CapyBro
Rewrite, fix, or translate text in any Windows app via a hotkey
CapyBro brings AI to your everyday text without switching to a browser tab. Select text in any Windows app — Word, Outlook, a browser field, VS Code, Telegram — press a global hotkey (Ctrl+Shift+E), and AI rewrites, fixes grammar, translates, or paraphrases it in place. Two backends: **OpenRouter** (cloud — GPT-4o, Claude, Gemini, DeepSeek, your own key) or **Ollama** (fully local/offline — text never leaves the machine). Native .NET 8 / WPF, ~48 MB, no Electron, zero telemetry. ... -
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TITTSE
Two Integrated Text To Speech Engines uses MMS & Silero
TITTSE is a Python Application that allows you to easily and quickly convert text to speech in 15 different languages (or add more easily) using Two TTS Engines. All you need is a text file ending in the tittse extension with 4 header lines including the TITTSE language code (see documentation for your language), the 'base' file name for the audio files TITTSE creates, voice gender (girl or boy), offset (file numbers added to base file name start at this number). After those first four lines, every paragraph is created as a single audio file. Install_TITTSE.sh is a Bash script that installs Python 3.1 and all needed dependencies in a virtual environment on your Linux system. ... -
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ChatGPT Retrieval Plugin
The ChatGPT Retrieval Plugin lets you easily find personal documents
...It can serve as a custom GPT plugin or function-calling backend so that a chat session can “look up” relevant documents based on user queries, inject those results into context, and respond more knowledgeably about a private knowledge base. The repo provides code for ingestion pipelines (embedding documents), APIs for querying, local server components, and privacy / PII detection modules. It also contains plugin manifest files (OpenAPI spec, plugin JSON) so that the retrieval backend can be registered in a plugin ecosystem. Because retrieval is often needed to make LLMs “know what’s in your docs” without leaking everything, this plugin aims to be a secure, flexible building block for retrieval-augmented generation (RAG) systems. -
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Adaptive Intelligence
Adaptive Intelligence also known as "Artificial General Intelligence"
Adaptive Intelligence is the implementation of neural science, forensic psychology , behavioral science with machine-learning and artificial intelligence to provide advanced automated software platforms with the ability to adjust and thrive in dynamic environments by combining cognitive flexibility, emotional regulation, resilience, and practical problem-solving skills. -
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GLM-4-32B-0414
Open Multilingual Multimodal Chat LMs
GLM-4-32B-0414 is a powerful open-source large language model featuring 32 billion parameters, designed to deliver performance comparable to leading models like OpenAI’s GPT series. It supports multilingual and multimodal chat capabilities with an extensive 32K token context length, making it ideal for dialogue, reasoning, and complex task completion. The model is pre-trained on 15 trillion tokens of high-quality data, including substantial synthetic reasoning datasets, and further enhanced... -
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TaskWeaver
A code-first agent framework for seamlessly planning analytics tasks
TaskWeaver is a multi-agent AI framework designed for orchestrating autonomous agents that collaborate to complete complex tasks. -
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Transformers in Time Series
A professionally curated list of awesome resources
Transformers in Time Series is a curated research repository that collects academic papers, code implementations, datasets, and learning resources related to transformer models for time series analysis. The project was created to systematically organize the rapidly growing research field that applies transformer architectures to time series modeling tasks. It compiles literature from major conferences and journals and categorizes them by application domains such as forecasting, anomaly detection, and classification. ... -
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Django friendly finite state machine
Django friendly finite state machine support
...FSM really helps to structure the code, especially when a new developer comes to the project. FSM is most effective when you use it for some sequential steps. Transition logging support could be achieved with help of django-fsm-log package. -
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Prompt Engineering Interactive Tutorial
Anthropic's Interactive Prompt Engineering Tutorial
...The course leans heavily on realistic failure modes (ambiguity, hallucination, brittle instructions) and shows how to iteratively debug prompts the way you would debug code. Lessons include building prompts from scratch for common tasks like extraction, classification, transformation, and step-by-step reasoning, with checkpoints that let you compare your outputs against solid baselines. You’ll also practice advanced patterns such as tool use, constrained generation, and response validation so outputs are trustworthy and machine-consumable. -
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Practical Machine Learning with Python
Master the essential skills needed to recognize and solve problems
Practical Machine Learning with Python is a comprehensive repository built to accompany a project-centered guide for applying machine learning techniques to real-world problems using Python’s mature data science ecosystem. It centralizes example code, datasets, model pipelines, and explanatory notebooks that teach users how to approach problems from data ingestion and cleaning all the way through feature engineering, model selection, evaluation, tuning, and production-ready deployment patterns. The repository emphasizes end-to-end workflows rather than isolated code snippets, showing how to handle common challenges like class imbalance, overfitting, hyperparameter optimization, and interpretability. ... -
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Machine Learning Notebooks
Machine Learning Notebooks
...The project focuses on delivering concise, well-structured Jupyter notebooks that demonstrate how to build, train, and evaluate models using modern machine learning frameworks such as PyTorch. Each notebook is intentionally lightweight, avoiding unnecessary complexity so that users can easily understand the core concepts and adapt the code to their own projects. The repository supports a wide range of applications, including natural language processing, computer vision, and general deep learning workflows. It is also designed to be easily extensible, allowing developers and researchers to build upon the provided examples without needing to restructure the codebase. -
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SolidGPT
Developer AI Persona Search Agent
SolidGPT is a AI searching assistant for developers that helps code and workspace semantic search. -
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A Survey of Surveys
A collection of 1000+ survey papers on Natural Language Processing
A Survey of Surveys is a large curated repository that collects and organizes survey papers related to natural language processing, machine learning, and artificial intelligence research. The project aims to provide a centralized index of survey literature that summarizes major developments across different subfields of AI. Rather than focusing on code implementations, the repository functions as an academic resource that helps researchers quickly discover comprehensive survey papers covering various topics. These topics include areas such as neural machine translation, language models, computer vision, and deep learning architectures. The repository organizes hundreds of papers into thematic categories and includes references, links, and bibliographic information to facilitate research and literature exploration.