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  • 1
    LEANN

    LEANN

    Local RAG engine for private multimodal knowledge search on devices

    LEANN is an open source system designed to enable retrieval-augmented generation (RAG) and semantic search across personal data while running entirely on local devices. It focuses on dramatically reducing the storage overhead typically required for vector search and embedding indexes, enabling efficient large-scale knowledge retrieval on consumer hardware. LEANN introduces a storage-efficient approximate nearest neighbor index combined with on-the-fly embedding recomputation to avoid storing...
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  • 2
    MLE-bench

    MLE-bench

    AI multi-agent framework for automating data-driven R&D workflows

    RD-Agent is an open source AI framework designed to automate research and development workflows in data-driven domains. It uses large language models and multiple collaborating agents to simulate the typical cycle of research, experimentation, and improvement that human data scientists follow. It separates the process into two core phases: a research stage that proposes hypotheses and ideas, and a development stage that implements and evaluates them through code execution and experiments. By...
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  • 3
    Semantra

    Semantra

    Multi-tool for semantic search

    Semantra is an open-source semantic search tool designed to help users explore large collections of documents by meaning rather than simple keyword matching. The software analyzes text and PDF documents stored locally and creates embeddings that allow queries to retrieve results based on conceptual similarity. It is primarily intended for individuals who need to extract insights from large document collections, including researchers, journalists, students, and historians. The system runs...
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  • 4
    deepjazz

    deepjazz

    Deep learning driven jazz generation using Keras & Theano

    deepjazz is a deep learning project that generates jazz music using recurrent neural networks trained on MIDI files. The repository demonstrates how machine learning can learn musical structure and produce original compositions. It uses the Keras and Theano libraries to build a two-layer Long Short-Term Memory network capable of learning temporal patterns in music. The system analyzes musical sequences from an input MIDI file and then generates new musical notes that follow similar stylistic...
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  • 5
    Python Code Tutorials

    Python Code Tutorials

    The Python Code Tutorials

    Python Code Tutorials is a large educational repository that aggregates programming tutorials from the “The Python Code” website into a structured collection of Python projects and learning materials. The repository covers a wide range of programming topics including cybersecurity, networking, web scraping, machine learning, GUI development, and automation scripts. Each tutorial typically includes complete Python code examples and explanations that demonstrate how to build real tools and...
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  • 6
    machine learning tutorials

    machine learning tutorials

    machine learning tutorials (mainly in Python3)

    machine-learning is a continuously updated repository documenting the author’s learning journey through data science and machine learning topics using practical tutorials and experiments. The project presents educational notebooks that combine mathematical explanations with code implementations using Python’s scientific computing ecosystem. Topics covered include classical machine learning algorithms, deep learning models, reinforcement learning, model deployment, and time-series analysis....
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  • 7
    AiLearning-Theory-Applying

    AiLearning-Theory-Applying

    Quickly get started with AI theory and practical applications

    AiLearning-Theory-Applying is a comprehensive educational repository designed to help learners quickly understand artificial intelligence theory and apply it in practical machine learning and deep learning projects. The repository provides extensive tutorials covering mathematical foundations, machine learning algorithms, deep learning concepts, and modern large language model architectures. It includes well-commented notebooks, datasets, and implementation examples that allow learners to...
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  • 8
    Ploomber

    Ploomber

    The fastest way to build data pipelines

    Ploomber is an open-source framework designed to simplify the development and deployment of data science and machine learning pipelines. It allows developers to transform exploratory data analysis workflows into production-ready pipelines without rewriting large portions of code. The system integrates with common development environments such as Jupyter Notebook, VS Code, and PyCharm, enabling data scientists to continue working with familiar tools while building scalable workflows. Ploomber...
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  • 9
    AutoTrain Advanced

    AutoTrain Advanced

    Faster and easier training and deployments

    AutoTrain Advanced is an open-source machine learning training framework developed by Hugging Face that simplifies the process of training and fine-tuning state-of-the-art AI models. The project provides a no-code and low-code interface that allows users to train models using custom datasets without needing extensive expertise in machine learning engineering. It supports a wide range of tasks including text classification, sequence-to-sequence modeling, token classification, sentence...
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  • 10
    newspaper4k

    newspaper4k

    Python library for scraping and analyzing online news articles easily

    Newspaper4k is a Python library designed for extracting, processing, and analyzing news articles from websites. It is a continuation and active fork of the original newspaper3k library, which had stopped receiving updates, with the goal of keeping the ecosystem maintained while adding improvements and bug fixes. It provides developers with tools to automatically download web pages, extract the main article content, and collect associated metadata such as titles, authors, images, and...
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  • 11
    videodl

    videodl

    Lightweight Python tool for downloading videos from many platforms

    Videodl is a lightweight video downloader implemented entirely in Python that allows users to retrieve videos from a wide range of online media platforms. It focuses on providing a fast and simple way to parse video pages and download media files, often prioritizing high-definition versions without watermarks when available. It supports numerous video platforms across both Chinese and international streaming ecosystems, enabling users to fetch content from many popular services through a...
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  • 12
    seq2seq-couplet

    seq2seq-couplet

    Play couplet with seq2seq model

    seq2seq-couplet is a deep learning application that generates Chinese couplet responses using a sequence-to-sequence model built with TensorFlow. Its purpose is not general machine translation, but a specialized text generation task in which the model produces a matching second line for a given first line in the style of traditional couplets. The repository includes the code needed to train the model, configure file paths and hyperparameters, and evaluate progress through loss and BLEU score...
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  • 13
    FlexLLMGen

    FlexLLMGen

    Running large language models on a single GPU

    FlexLLMGen is an open-source inference engine designed to run large language models efficiently on limited hardware resources such as a single GPU. The system focuses on high-throughput generation workloads where large batches of text must be processed quickly, such as large-scale data extraction or document analysis tasks. Instead of requiring expensive multi-GPU systems, the framework uses techniques such as memory offloading, compression, and optimized batching to run large models on...
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  • 14
    Transfer Learning Repo

    Transfer Learning Repo

    Transfer learning / domain adaptation / domain generalization

    Transfer Learning Repo is an open-source repository that compiles resources, code implementations, and academic references related to transfer learning and its related research areas. The project functions as a large knowledge hub that organizes papers, tutorials, datasets, and software implementations across topics such as domain adaptation, domain generalization, multi-task learning, and few-shot learning. The repository includes surveys and theoretical explanations that help readers...
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  • 15
    verl-agent

    verl-agent

    Designed for training LLM/VLM agents via RL

    verl-agent is an open-source reinforcement learning framework designed to train large language model agents and vision-language model agents for complex interactive environments. Built as an extension of the veRL reinforcement learning infrastructure, the project focuses on enabling scalable training for agents that perform multi-step reasoning and decision-making tasks. The framework supports multi-turn interactions between agents and their environments, allowing the system to receive...
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  • 16
    Pydoll

    Pydoll

    Async Python library in automating Chromium browsers without WebDriver

    Pydoll is a Python library designed for automating Chromium-based web browsers such as Chrome and Edge without relying on a traditional WebDriver layer. Instead of using external drivers, it connects directly to the Chrome DevTools Protocol through WebSocket, allowing scripts to control browser behavior more efficiently and with fewer compatibility issues. It provides a high-level API that simplifies common browser automation tasks while still offering access to low-level protocol features...
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  • 17
    MING

    MING

    A large-scale model of medical consultation in Chinese

    MING is an open-source medical large language model designed for intelligent medical consultation and question answering in Chinese. The project focuses on building a healthcare-focused conversational system capable of responding to medical questions, analyzing case descriptions, and guiding diagnostic reasoning. It is trained using medical instruction tuning so that the model can understand patient symptoms and respond with structured explanations and clinical suggestions. One of its...
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  • 18
    LLM-Pruner

    LLM-Pruner

    On the Structural Pruning of Large Language Models

    LLM-Pruner is an open-source framework designed to compress large language models through structured pruning techniques while maintaining their general capabilities. Large language models often require enormous computational resources, making them expensive to deploy and inefficient for many practical applications. LLM-Pruner addresses this issue by identifying and removing non-essential components within transformer architectures, such as redundant attention heads or feed-forward...
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  • 19
    SAG

    SAG

    SQL-Driven RAG Engine

    SAG is an open-source SQL-driven retrieval-augmented generation engine that dynamically constructs knowledge graphs during query processing. Instead of relying on a static knowledge graph prepared in advance, the system automatically builds relational structures between entities while processing user queries. Documents are first decomposed into atomic semantic events, which are then represented using multidimensional natural language vectors. These vectors allow the system to identify...
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  • 20
    Prompt Poet

    Prompt Poet

    Streamlines and simplifies prompt design for both developers

    Prompt Poet is an open-source framework designed to simplify the creation, organization, and maintenance of prompts for large language model applications. The project focuses on transforming prompt engineering into a structured design process rather than ad-hoc string manipulation within application code. It allows developers and non-technical users to build prompts using templated configurations based on YAML and Jinja2, which makes prompts easier to compose, reuse, and modify across...
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  • 21
    AICGSecEval

    AICGSecEval

    A.S.E (AICGSecEval) is a repository-level AI-generated code security

    AICGSecEval is an open-source benchmark framework designed to evaluate the security of code generated by artificial intelligence systems. The project was developed to address concerns that AI-assisted programming tools may produce insecure code containing vulnerabilities such as injection flaws or unsafe logic. The framework constructs evaluation tasks based on real-world software repositories and known vulnerability cases derived from CVE records. By simulating realistic development...
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  • 22
    Text-to-LoRA (T2L)

    Text-to-LoRA (T2L)

    Hypernetworks that adapt LLMs for specific benchmark tasks

    Text-to-LoRA is a research project that introduces a method for dynamically adapting large language models using hypernetworks that generate LoRA parameters directly from textual descriptions. Instead of training a new LoRA adapter for every task or dataset, the system can produce task-specific adaptations based solely on a text description of the desired capability. This approach enables models to rapidly internalize new contextual knowledge without performing traditional fine-tuning steps....
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  • 23
    AgentEvolver

    AgentEvolver

    Towards Efficient Self-Evolving Agent System

    AgentEvolver is an open-source research framework for building self-evolving AI agents powered by large language models. The system focuses on improving the efficiency and scalability of training autonomous agents by allowing them to generate tasks, explore environments, and refine strategies without heavy reliance on manually curated datasets. Its architecture combines reinforcement learning with LLM-driven reasoning mechanisms to guide exploration and learning. The framework introduces...
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  • 24
    DriveLM

    DriveLM

    Driving with Graph Visual Question Answering

    DriveLM is a research-oriented framework and dataset designed to explore how vision-language models can be integrated into autonomous driving systems. The project introduces a new paradigm called graph visual question answering that structures reasoning about driving scenes through interconnected tasks such as perception, prediction, planning, and motion control. Instead of treating autonomous driving as a purely sensor-driven pipeline, DriveLM frames it as a reasoning problem where models...
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  • 25
    E2B Desktop Sandbox

    E2B Desktop Sandbox

    E2B Desktop Sandbox for LLMs. E2B Sandbox

    E2B Desktop is an open-source sandboxed virtual desktop environment designed to enable secure “computer use” by large language models and automated agents. The platform provides isolated virtual machines where applications can be executed safely without affecting the host system. Each sandbox runs independently and can be configured with custom dependencies or tools required by an AI agent or automation workflow. The system allows developers to programmatically create and control these...
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