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  • 1
    OpenOutreach

    OpenOutreach

    Linkedin Automation Tool

    ...The system generates search queries, evaluates candidate profiles, and learns over time which contacts best match the ideal customer profile. According to the repository, it combines large language model classification with a Bayesian machine learning layer based on profile embeddings, which helps it shift from broad exploration to more confident qualification as it gathers more decisions. It is designed to automate personalized outreach as well, including connection requests and follow-up messaging, while keeping deployment under the user’s control through a local or self-hosted setup.
    Downloads: 0 This Week
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  • 2
    SeaGOAT

    SeaGOAT

    local-first semantic code search engine

    ...Instead of relying solely on traditional keyword search, it uses vector embeddings to represent the meaning of code and queries, allowing users to perform semantic searches that find relevant code even when the exact keywords are not present. The tool runs locally on a developer’s machine and processes repositories using a combination of embedding models and conventional search utilities, enabling both semantic and text-based retrieval methods. By combining vector search with tools like ripgrep, SeaGOAT provides a hybrid approach that supports both natural language queries and precise keyword matching in source files. ...
    Downloads: 0 This Week
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  • 3
    RLHF-Reward-Modeling

    RLHF-Reward-Modeling

    Recipes to train reward model for RLHF

    ...In RLHF pipelines, reward models are responsible for evaluating generated responses and assigning scores that guide the model toward outputs that better match human preferences. The repository provides training recipes and implementations for building reward and preference models using modern machine learning frameworks. It supports multiple optimization strategies commonly used in alignment pipelines, including reinforcement learning with PPO, iterative supervised fine-tuning using rejection sampling, and direct preference optimization methods. The project also includes evaluation results showing that the trained reward models can achieve competitive performance compared with other open-source alignment systems.
    Downloads: 0 This Week
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  • 4
    Pixeltable

    Pixeltable

    Data Infrastructure providing an approach to multimodal AI workloads

    Pixeltable is an open-source Python data infrastructure framework designed to support the development of multimodal AI applications. The system provides a declarative interface for managing the entire lifecycle of AI data pipelines, including storage, transformation, indexing, retrieval, and orchestration of datasets. Unlike traditional architectures that require multiple tools such as databases, vector stores, and workflow orchestrators, Pixeltable unifies these functions within a...
    Downloads: 0 This Week
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  • 5
    AI Powered Knowledge Graph Generator

    AI Powered Knowledge Graph Generator

    AI Powered Knowledge Graph Generator

    AI-Powered Knowledge Graph is an open-source project focused on building knowledge graph systems that integrate artificial intelligence and machine learning to represent complex relationships between data entities. Knowledge graphs organize information as networks of nodes and relationships, allowing applications to analyze connections between concepts, datasets, or real-world entities. By incorporating AI techniques such as natural language processing and semantic reasoning, the project enables systems to automatically extract relationships and insights from large volumes of data. ...
    Downloads: 0 This Week
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  • 6
    xLSTM

    xLSTM

    Neural Network architecture based on ideas of the original LSTM

    xLSTM is an open-source machine learning architecture that reimagines the classic Long Short-Term Memory (LSTM) network for modern large-scale language modeling and sequence processing tasks. The project introduces a new recurrent neural network design that incorporates exponential gating mechanisms and enhanced memory structures to overcome limitations of traditional LSTM models.
    Downloads: 0 This Week
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  • 7
    MaxText

    MaxText

    A simple, performant and scalable Jax LLM

    ...MaxText includes ready-to-use configurations and reproducible training examples that help developers understand how to deploy large-scale AI workloads with modern machine learning infrastructure.
    Downloads: 0 This Week
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  • 8
    HuixiangDou

    HuixiangDou

    Overcoming Group Chat Scenarios with LLM-based Technical Assistance

    ...This design allows the system to participate in group discussions without flooding the chat with unnecessary messages. The assistant uses retrieval and ranking methods along with language model reasoning to produce accurate answers for technical topics such as computer vision and machine learning projects. It can be integrated into messaging platforms such as WeChat or other team collaboration tools to assist developer communities.
    Downloads: 0 This Week
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  • 9
    Chitu

    Chitu

    High-performance inference framework for large language models

    ...It supports heterogeneous computing environments, including CPUs, GPUs, and various specialized AI accelerators, allowing models to run across a wide range of infrastructure configurations. Chitu is designed to scale from small single-machine deployments to large distributed clusters that handle high volumes of concurrent inference requests. The system also includes performance optimizations for large models, including support for quantized formats and efficient computation operators that reduce memory usage and latency. Its architecture aims to support enterprise adoption by ensuring stable long-term operation under production workloads.
    Downloads: 0 This Week
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    MyQ Print Management Software

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  • 10
    Sparrow

    Sparrow

    Structured data extraction and instruction calling with ML, LLM

    Sparrow is an open-source platform designed to extract structured information from documents, images, and other unstructured data sources using machine learning and large language models. The system focuses on transforming complex documents such as invoices, receipts, forms, and scanned pages into structured formats like JSON that can be processed by downstream applications. It combines several components, including OCR pipelines, vision-language models, and LLM-based reasoning modules to identify and extract meaningful data fields from heterogeneous document layouts. ...
    Downloads: 0 This Week
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  • 11
    Anomaly Detection Learning Resources

    Anomaly Detection Learning Resources

    Anomaly detection related books, papers, videos, and toolboxes

    ...It includes materials covering a wide range of anomaly detection domains, including time series data, graph data, tabular datasets, and real-time monitoring systems. By compiling resources from multiple programming ecosystems such as Python, R, and other machine learning platforms, the repository allows users to discover both research papers and practical implementations.
    Downloads: 0 This Week
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  • 12
    hCaptcha Challenger

    hCaptcha Challenger

    Gracefully face hCaptcha challenge with multimodal llms

    hCaptcha Challenger is an open-source automation framework designed to solve hCaptcha verification challenges using computer vision models and multimodal reasoning techniques. The project integrates machine learning models capable of analyzing visual captcha tasks and identifying the correct responses required to pass the verification process. Instead of relying on third-party captcha-solving services or browser scripts, the system operates independently by using pretrained neural networks that can classify images, detect objects, and interpret spatial relationships. ...
    Downloads: 0 This Week
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  • 13
    Grok-1

    Grok-1

    Open-source, high-performance Mixture-of-Experts large language model

    ...In March 2024, xAI released Grok-1's model weights and architecture under the Apache 2.0 license, making them openly accessible to developers. The accompanying GitHub repository provides JAX example code for loading and running the model. Due to its substantial size, utilizing Grok-1 requires a machine with significant GPU memory. The repository's MoE layer implementation prioritizes correctness over efficiency, avoiding the need for custom kernels. This is a full repo snapshot ZIP file of the Grok-1 code.
    Downloads: 35 This Week
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  • 14
    offyai

    offyai

    OffyAI — Local AI. Private by Design. Built for Your Machine.

    OffyAI is a modern local-first AI desktop application that brings a ChatGPT-like experience to your computer while keeping your AI workloads close to you. It is designed for users who want to run, manage, and interact with local Large Language Models (LLMs) through a clean desktop interface without depending entirely on cloud-based AI services.
    Downloads: 1 This Week
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  • 15
    chatd

    chatd

    Chat with your documents using local AI

    chatd is an open-source desktop application that allows users to interact with their documents through a locally running large language model. The software focuses on privacy and security by ensuring that all document processing and inference occur entirely on the user’s computer without sending data to external cloud services. It includes a built-in integration with the Ollama runtime, which provides a cross-platform environment for running large language models locally. The application...
    Downloads: 1 This Week
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  • 16
    AIConfig

    AIConfig

    AIConfig is a config-based framework to build generative AI apps

    ...The framework allows prompts, model configurations, and parameters to be stored as structured configuration files that can be version controlled and managed independently from the rest of the software system. This approach improves collaboration between developers, prompt engineers, and machine learning practitioners by turning prompt logic into a reusable and editable artifact. AIConfig supports multiple model providers and modalities, enabling developers to experiment with different models without rewriting application logic. The configuration format is JSON-serializable and integrates with tools such as Python and Node SDKs, allowing the same configuration file to be used across multiple environments.
    Downloads: 0 This Week
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  • 17
    Firefly LLM

    Firefly LLM

    A large model training tool that supports training large models

    ...The project provides a comprehensive environment where developers can perform tasks such as model pre-training, instruction tuning, and preference optimization using widely adopted machine learning techniques. Its architecture supports both full-parameter training and parameter-efficient strategies like LoRA and QLoRA, making it suitable for environments with limited computational resources. Firefly is compatible with a wide range of popular open-source models including LLaMA, Qwen, Baichuan, InternLM, and Mistral, enabling developers to experiment with different architectures using a consistent training pipeline. ...
    Downloads: 0 This Week
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  • 18
    towhee

    towhee

    Framework that is dedicated to making neural data processing

    Towhee is an open-source machine-learning pipeline that helps you encode your unstructured data into embeddings. You can use our Python API to build a prototype of your pipeline and use Towhee to automatically optimize it for production-ready environments. From images to text to 3D molecular structures, Towhee supports data transformation for nearly 20 different unstructured data modalities.
    Downloads: 1 This Week
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  • 19
    ReplitLM

    ReplitLM

    Inference code and configs for the ReplitLM model family

    ReplitLM is a family of open-source language models developed by Replit for assisting with programming tasks such as code generation and completion. The project includes model checkpoints, configuration files, and example code that enable developers to run and experiment with the models locally or within machine learning frameworks. These models are designed specifically for coding workflows and are trained on large datasets of source code covering many programming languages and development environments. The repository also includes documentation and tutorials for integrating the models into development tools, APIs, or research pipelines. ...
    Downloads: 0 This Week
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  • 20
    LLM Training Puzzles

    LLM Training Puzzles

    What would you do with 1000 H100s

    LLM Training Puzzles is a notebook-based collection of eight exercises about training large neural networks across many GPUs. It introduces the core primitives behind distributed language model training without requiring access to a thousand-machine cluster. The puzzles focus on memory efficiency, communication, partitioning, and compute pipelining. Learners work through simplified scenarios that expose the tradeoffs hidden inside large training systems. The hands-on format emphasizes deriving behavior rather than memorizing framework commands. Google Colab is recommended so readers can copy the notebook and begin experimenting quickly. ...
    Downloads: 0 This Week
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  • 21
    Genoss GPT

    Genoss GPT

    One API for all LLMs either Private or Public

    One line replacement for openAI ChatGPT & Embeddings powered by OSS models. Genoss is a pioneering open-source initiative that aims to offer a seamless alternative to OpenAI models such as GPT 3.5 & 4, using open-source models like GPT4ALL.
    Downloads: 0 This Week
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  • 22
    Alpa

    Alpa

    Training and serving large-scale neural networks

    Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code.
    Downloads: 0 This Week
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  • 23
    LocalLLM Studio

    LocalLLM Studio

    Chat with local GGUF LLMs on your own machine

    Chat with local GGUF LLMs on your own machine — private, offline, model-agnostic. LLM Apps & Agents Apache-2.0 v1.0.5 100% AI-built 0 0 Get LocalLLM Studio View source Website Run open-weight language models (GGUF) fully offline on your own hardware via llama.cpp: a chat interface with system prompts, conversation history, adjustable sampling, and simple retrieval over your own files.
    Downloads: 0 This Week
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