Search Results for "bingo python code" - Page 2
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Showing 104 open source projects for "bingo python code"
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Rezku Point of SaleRezku is an all-inclusive ordering platform and management solution for all types of restaurant and bar concepts. You can now get a fully custom branded downloadable smartphone ordering app for your restaurant exclusively from Rezku.
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AestheticsPro Medical Spa SoftwareAestheticsPro is the most complete Aesthetics Software on the market today. HIPAA Cloud Compliant with electronic charting, integrated POS, targeted marketing and results driven reporting; AestheticsPro delivers the tools you need to manage your medical spa business. It is our mission To Provide an All-in-One Cutting Edge Software to the Aesthetics Industry.
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Ludwig AI
Low-code framework for building custom LLMs, neural networks
Declarative deep learning framework built for scale and efficiency. Ludwig is a low-code framework for building custom AI models like LLMs and other deep neural networks. Declarative YAML configuration file is all you need to train a state-of-the-art LLM on your data. Support for multi-task and multi-modality learning. Comprehensive config validation detects invalid parameter combinations and prevents runtime failures. Automatic batch size selection, distributed training (DDP, DeepSpeed),... -
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Qwen
The official repo of Qwen chat & pretrained large language model
Qwen is a series of large language models developed by Alibaba Cloud, consisting of various pretrained versions like Qwen-1.8B, Qwen-7B, Qwen-14B, and Qwen-72B. These models, which range from smaller to larger configurations, are designed for a wide range of natural language processing tasks. They are openly available for research and commercial use, with Qwen's code and model weights shared on GitHub. Qwen's capabilities include text generation, comprehension, and conversation, making it a... -
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llms-from-scratch-cn
Build a large language model from 0 only with Python foundation
...Through a collection of notebooks, code examples, and translated learning materials, users can explore how to implement components such as multi-head attention, data loaders, and training pipelines using Python and PyTorch. -
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CodeGen
Open-source model for program synthesis
CodeGen is a family of open-source large language models designed specifically for program synthesis and code generation tasks. Developed by Salesforce Research, the models are trained on large datasets containing both natural language and programming language content. This allows them to translate natural language descriptions into functional code across a variety of programming languages. CodeGen supports multi-turn program synthesis, meaning it can generate complex programs through a... -
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DocETL
A system for agentic LLM-powered data processing and ETL
DocETL is an open-source system designed to build and execute data processing pipelines powered by large language models, particularly for analyzing complex collections of documents and unstructured datasets. The platform allows developers and researchers to construct structured workflows that extract, transform, and organize information from sources such as reports, transcripts, legal documents, and other text-heavy data. Instead of relying on single prompts or ad-hoc scripts, DocETL... -
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SimpleLLM
950 line, minimal, extensible LLM inference engine built from scratch
SimpleLLM is a minimal, extensible large language model inference engine implemented in roughly 950 lines of code, built from scratch to serve both as a learning tool and a research platform for novel inference techniques. It provides the core components of an LLM runtime—such as tokenization, batching, and asynchronous execution—without the abstraction overhead of more complex engines, making it easier for developers and researchers to understand and modify. Designed to run efficiently on... -
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AI-Codereview-Gitlab
GitLab automatic code review tool based on large models
AI-Codereview-Gitlab is an open-source automation tool that integrates large language models into the GitLab development workflow to perform automated code reviews. The system monitors GitLab repositories and analyzes commits or merge requests using AI models to identify potential issues, coding mistakes, and quality improvements before the code is merged. By leveraging multiple large language model providers—including OpenAI, DeepSeek, ZhipuAI, or local models through Ollama—the platform... -
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LLMs-from-scratch
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
LLMs-from-scratch is an educational codebase that walks through implementing modern large-language-model components step by step. It emphasizes building blocks—tokenization, embeddings, attention, feed-forward layers, normalization, and training loops—so learners understand not just how to use a model but how it works internally. The repository favors clear Python and NumPy or PyTorch implementations that can be run and modified without heavyweight frameworks obscuring the logic. Chapters... -
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MathModelAgent
An Agent Designed for Mathematical Modeling
MathModelAgent is an AI agent system designed specifically for assisting with mathematical modeling tasks and academic problem solving. The platform automates the process of analyzing mathematical problems, constructing models, generating code for simulations or computations, and producing a complete research-style report. The project uses a multi-agent architecture where different specialized agents handle tasks such as problem interpretation, modeling design, programming implementation,... -
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Sage Chat
Chat with any codebase in under two minutes | Fully local
Sage is an open-source AI developer assistant designed to help engineers understand and work with complex codebases more effectively. The tool functions similarly to an intelligent research agent that can analyze a repository and answer questions about how the software works. Instead of focusing solely on code generation, Sage emphasizes code comprehension, system architecture analysis, and integration guidance. Developers can ask natural language questions about a project, and the system... -
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ai-cookbook
Examples and tutorials to help developers build AI systems
ai-cookbook is an open-source repository that provides practical tutorials, code examples, and reusable snippets designed to help developers build real-world artificial intelligence applications quickly. The project focuses on delivering hands-on engineering guidance rather than theoretical explanations, allowing developers to copy, adapt, and integrate working code directly into their own systems. The repository contains examples that demonstrate how to build AI workflows using modern tools... -
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MLC LLM
Universal LLM Deployment Engine with ML Compilation
MLC LLM is a machine learning compiler and deployment framework designed to enable efficient execution of large language models across a wide range of hardware platforms. The project focuses on compiling models into optimized runtimes that can run natively on devices such as GPUs, mobile processors, browsers, and edge hardware. By leveraging machine learning compilation techniques, mlc-llm produces high-performance inference engines that maintain consistent APIs across platforms. The system... -
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Qwen3
Qwen3 is the large language model series developed by Qwen team
Qwen3 is a cutting-edge large language model (LLM) series developed by the Qwen team at Alibaba Cloud. The latest updated version, Qwen3-235B-A22B-Instruct-2507, features significant improvements in instruction-following, reasoning, knowledge coverage, and long-context understanding up to 256K tokens. It delivers higher quality and more helpful text generation across multiple languages and domains, including mathematics, coding, science, and tool usage. Various quantized versions,... -
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SentenceTransformers
Multilingual sentence & image embeddings with BERT
...The framework is based on PyTorch and Transformers and offers a large collection of pre-trained models tuned for various tasks. Further, it is easy to fine-tune your own models. Our models are evaluated extensively and achieve state-of-the-art performance on various tasks. Further, the code is tuned to provide the highest possible speed. -
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LongBench
LongBench v2 and LongBench (ACL 25'&24')
LongBench is a comprehensive benchmark designed to evaluate the ability of large language models to understand and reason over very long textual contexts. Traditional language model benchmarks typically evaluate tasks involving relatively short inputs, which does not reflect many real-world applications such as analyzing large documents or entire code repositories. LongBench addresses this gap by providing datasets that require models to process and reason over long sequences of text across... -
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vim-ai
AI-powered code assistant for Vim. OpenAI and ChatGPT plugin for Vim
vim-ai is an AI-powered assistant plugin for Vim and Neovim that brings language-model features directly into the editor. It allows users to generate code or text, edit selections in place, and carry on interactive chat-style conversations without leaving the terminal editing environment. The plugin is built around OpenAI-compatible APIs, which means it can work not only with OpenAI itself but also with compatible proxies and alternative providers. Its command set covers text completion,... -
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langrocks
Tools like web browser, computer access and code runner for LLMs
Langrocks is a programming language experimentation toolkit that enables developers to create, test, and optimize custom programming languages. -
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H2O LLM Studio
Framework and no-code GUI for fine-tuning LLMs
Welcome to H2O LLM Studio, a framework and no-code GUI designed for fine-tuning state-of-the-art large language models (LLMs). You can also use H2O LLM Studio with the command line interface (CLI) and specify the configuration file that contains all the experiment parameters. To finetune using H2O LLM Studio with CLI, activate the pipenv environment by running make shell. With H2O LLM Studio, training your large language model is easy and intuitive. First, upload your dataset and then start... -
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ChatGLM-6B
ChatGLM-6B: An Open Bilingual Dialogue Language Model
ChatGLM-6B is an open bilingual (Chinese + English) conversational language model based on the GLM architecture, with approximately 6.2 billion parameters. The project provides inference code, demos (command line, web, API), quantization support for lower memory deployment, and tools for finetuning (e.g., via P-Tuning v2). It is optimized for dialogue and question answering with a balance between performance and deployability in consumer hardware settings. Support for quantized inference... -
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GLM-4.5
GLM-4.5: Open-source LLM for intelligent agents by Z.ai
GLM-4.5 is a cutting-edge open-source large language model designed by Z.ai for intelligent agent applications. The flagship GLM-4.5 model has 355 billion total parameters with 32 billion active parameters, while the compact GLM-4.5-Air version offers 106 billion total parameters and 12 billion active parameters. Both models unify reasoning, coding, and intelligent agent capabilities, providing two modes: a thinking mode for complex reasoning and tool usage, and a non-thinking mode for... -
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Strix
Open-source AI hackers to find and fix your app’s vulnerabilities
Strix is an open source agent-driven security platform that uses autonomous AI agents to identify, investigate, and validate vulnerabilities in software applications. The system is designed to mimic the behavior of real attackers by executing dynamic testing and verifying findings through proof-of-concept exploitation. Unlike traditional vulnerability scanners that rely heavily on static analysis, Strix agents actively run code, probe systems, and attempt exploitation to confirm whether... -
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LLM Foundry
LLM training code for MosaicML foundation models
Introducing MPT-7B, the first entry in our MosaicML Foundation Series. MPT-7B is a transformer trained from scratch on 1T tokens of text and code. It is open source, available for commercial use, and matches the quality of LLaMA-7B. MPT-7B was trained on the MosaicML platform in 9.5 days with zero human intervention at a cost of ~$200k. Large language models (LLMs) are changing the world, but for those outside well-resourced industry labs, it can be extremely difficult to train and deploy... -
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Awesome LLM Apps
Collection of awesome LLM apps with AI Agents and RAG using OpenAI
Awesome LLM Apps is a community-curated directory of interesting, practical, and innovative applications built on or around large language models, serving as a discovery hub for developers, researchers, and enthusiasts. The list spans a wide range of categories including productivity tools, creative assistants, utilities, education platforms, research frameworks, and niche vertical apps, showcasing how generative models are being used across domains. Each entry includes a brief description,... -
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Ling
Ling is a MoE LLM provided and open-sourced by InclusionAI
Ling is a Mixture-of-Experts (MoE) large language model (LLM) provided and open-sourced by inclusionAI. The project offers different sizes (Ling-lite, Ling-plus) and emphasizes flexibility and efficiency: being able to scale, adapt expert activation, and perform across a range of natural language/reasoning tasks. Example scripts, inference pipelines, and documentation. The codebase includes inference, examples, models, documentation, and model download infrastructure. As more developers and... -
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VibeThinker
Diversity-driven optimization and large-model reasoning ability
VibeThinker is a compact but high-capability open-source language model released by WeiboAI (Sina AI Lab). It contains about 1.5 billion parameters, far smaller than many “frontier” models, yet it is explicitly optimized for reasoning, mathematics, and code generation tasks rather than general open-domain chat. The innovation lies in its training methodology: the team uses what they call the Spectrum-to-Signal Principle (SSP), where a first stage emphasizes diversity of reasoning paths (the...
