Showing 744 open source projects for "framework"

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  • 1
    NNCF

    NNCF

    Neural Network Compression Framework for enhanced OpenVINO

    NNCF (Neural Network Compression Framework) is an optimization toolkit for deep learning models, designed to apply quantization, pruning, and other techniques to improve inference efficiency.
    Downloads: 0 This Week
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  • 2
    HRM-Text

    HRM-Text

    1B text generation model based on the HRM architecture

    HRM-Text is a one-billion-parameter text generation model and pretraining framework based on the Hierarchical Reasoning Model architecture. It is designed to make foundation model pretraining more accessible by reducing compute and data requirements compared with traditional scaling-heavy approaches. The system combines hierarchical recurrent design, task-completion strengthening, and latent-space reasoning. Its training stack includes PrefixLM sequence packing, FlashAttention 3 kernels, PyTorch FSDP2, evaluation scripts, and checkpoint conversion tools. ...
    Downloads: 1 This Week
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  • 3
    AI-Trader

    AI-Trader

    100% Fully-Automated Agent-Native Trading

    ...The framework supports modular components for portfolio analysis, signal generation, market reasoning, and trading automation, allowing users to customize workflows for different trading styles and asset classes. AI-Trader also emphasizes extensibility for integrating external APIs, datasets, and custom models.
    Downloads: 1 This Week
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  • 4
    SWIFT LLM

    SWIFT LLM

    Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs

    ...The framework also includes support for many modern training strategies, including preference learning methods and parameter-efficient fine-tuning techniques. ms-swift is designed to work with hundreds of language and multimodal models, providing a unified environment for experimentation and production deployment.
    Downloads: 1 This Week
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  • 5
    Arcade AI

    Arcade AI

    Arcade Tool Development Kit (TDK), Worker, Evals, and CLI

    ...Core platform functionality and schemas. This repository contains the core Arcade libraries, organized as separate packages for maximum flexibility and modularity. Evaluation framework for testing tool performance. Test your MCP server's tools, resources, prompts, elicitation, and OAuth 2. MCPJam is compliant with the latest MCP specs. Connect to any MCP server. MCPJam inspector supports STDIO, SSE, and Streamable HTTP transports.
    Downloads: 1 This Week
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  • 6
    kotaemon

    kotaemon

    An open-source RAG-based tool for chatting with your documents

    An open-source clean & customizable RAG UI for chatting with your documents. Built with both end users and developers in mind. This project serves as a functional RAG UI for both end users who want to do QA on their documents and developers who want to build their own RAG pipeline.
    Downloads: 7 This Week
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  • 7
    Chemprop

    Chemprop

    Message Passing Neural Networks for Molecule Property Prediction

    Chemprop is a repository containing message-passing neural networks for molecular property prediction.
    Downloads: 2 This Week
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  • 8
    Claude Code Plugins

    Claude Code Plugins

    Intelligent automation and multi-agent orchestration for Claude Code

    Claude Code Plugins is a lightweight framework designed to define, manage, and execute AI agents in a modular and extensible way, typically focusing on orchestrating tasks using large language models and tool integrations. The project provides abstractions for building agents that can interpret instructions, execute commands, and interact with external systems in a structured workflow.
    Downloads: 0 This Week
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  • 9
    OpenSage

    OpenSage

    An agent framework that enables AI to create their own agent

    ...The framework is built around the concept of an Agent Development Kit (ADK), providing structured components for memory, reasoning, and task decomposition while allowing agents to iteratively improve their own design. A key innovation is its hierarchical and graph-based memory system, which enables agents to store, retrieve, and organize information across complex workflows with improved efficiency and contextual awareness.
    Downloads: 0 This Week
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  • 10
    Solace Agent Mesh

    Solace Agent Mesh

    An event-driven framework designed to build multi-agent AI systems

    Solace Agent Mesh is an event-driven framework designed to build, orchestrate, and scale multi-agent AI systems where specialized agents collaborate to solve complex tasks across distributed environments. It addresses one of the main challenges in modern AI systems, which is connecting isolated agents, data sources, and enterprise systems into a cohesive and interoperable ecosystem.
    Downloads: 0 This Week
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  • 11
    ShortGPT

    ShortGPT

    AI framework for automated short video creation and editing tools

    ShortGPT is an experimental AI-powered framework designed to automate the creation of short-form and long-form video content. It provides a structured system that handles multiple stages of the content creation workflow, including script generation, asset sourcing, voiceover synthesis, and video editing. ShortGPT uses large language models to generate scripts and prompts that guide the automated editing and production process.
    Downloads: 0 This Week
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  • 12
    C3

    C3

    The goal of CLAIMED is to enable low-code/no-code rapid prototyping

    C3 is an open-source framework designed to simplify the development and deployment of data science and machine learning workflows through reusable components and low-code development techniques. The framework focuses on enabling rapid prototyping while maintaining a path to production through automated CI/CD integration. CLAIMED provides a component-based architecture where data processing steps, models, and workflows can be packaged into reusable operators.
    Downloads: 0 This Week
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  • 13
    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. ...
    Downloads: 0 This Week
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  • 14
    Ploomber

    Ploomber

    The fastest way to build data pipelines

    ...Ploomber automatically manages task dependencies and execution order, allowing complex pipelines with multiple stages to run reliably. The framework can deploy pipelines across different computing environments including Kubernetes, Airflow, AWS Batch, and high-performance computing clusters. It also helps teams maintain reproducibility by tracking changes in code and rerunning only outdated pipeline tasks.
    Downloads: 0 This Week
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  • 15
    LLM-Pruner

    LLM-Pruner

    On the Structural Pruning of Large Language Models

    ...The framework relies on gradient-based analysis to determine which parameters contribute least to model performance, enabling targeted structural pruning rather than simple weight removal. After pruning, the framework applies lightweight fine-tuning methods such as LoRA to recover performance using relatively small datasets and short training times.
    Downloads: 0 This Week
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  • 16
    Prompt Poet

    Prompt Poet

    Streamlines and simplifies prompt design for both developers

    ...By separating prompt structure from program logic, Prompt Poet encourages iterative prompt design and experimentation without requiring constant changes to application code. The framework supports dynamic prompts that adapt to runtime data, allowing developers to inject variables, context, and examples directly into templates. This approach is particularly useful in production environments where prompt consistency, maintainability, and versioning are important.
    Downloads: 0 This Week
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  • 17
    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.
    Downloads: 0 This Week
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  • 18
    AgentEvolver

    AgentEvolver

    Towards Efficient Self-Evolving Agent System

    ...The framework introduces several key mechanisms, including self-questioning to create new learning tasks, self-navigating to improve exploration through experience reuse, and self-attributing to assign rewards based on the usefulness of actions. These mechanisms enable agents to continuously improve their capabilities while interacting with complex environments and tools.
    Downloads: 0 This Week
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  • 19
    KVCache-Factory

    KVCache-Factory

    Unified KV Cache Compression Methods for Auto-Regressive Models

    KVCache-Factory is an open-source research framework designed to explore and implement unified key-value cache compression techniques for autoregressive transformer models. In large language models, the key-value cache stores intermediate attention states that enable efficient token generation during inference, but these caches can consume large amounts of GPU memory when handling long contexts.
    Downloads: 0 This Week
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  • 20
    ReCall

    ReCall

    Learning to Reason with Search for LLMs via Reinforcement Learning

    ...Instead of relying purely on static knowledge stored inside the model, ReCall allows the language model to dynamically decide when it should retrieve information or invoke external capabilities during the reasoning process. The framework uses reinforcement learning to train models to perform these tool calls effectively while solving multi-step reasoning tasks.
    Downloads: 0 This Week
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  • 21
    ControlFlow

    ControlFlow

    Take control of your AI agents

    ControlFlow is an open-source Python framework developed to help engineers design and orchestrate agentic workflows powered by large language models. The framework provides a structured approach for building AI systems by breaking complex tasks into smaller units called tasks that can be assigned to specialized AI agents. Developers can combine these tasks into flows that define how work is executed, enabling the creation of multi-step reasoning pipelines and collaborative agent systems. ...
    Downloads: 0 This Week
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  • 22
    CAG

    CAG

    Cache-Augmented Generation: A Simple, Efficient Alternative to RAG

    ...This strategy allows the model to generate responses using the cached context directly, eliminating the need for repeated retrieval operations during runtime. As a result, the approach can significantly reduce latency and simplify system architecture compared with traditional RAG pipelines. The framework is particularly effective when the knowledge base is limited enough to fit within the extended context window of modern language models.
    Downloads: 0 This Week
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  • 23
    PRIME

    PRIME

    Scalable RL solution for advanced reasoning of language models

    ...PRIME provides training pipelines, datasets, and experimental infrastructure that allow researchers to train models with reinforcement learning tailored for reasoning improvement. The framework also includes data preprocessing utilities and example datasets such as mathematical reasoning tasks that are well suited for process-based reward signals.
    Downloads: 0 This Week
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  • 24
    Agentic Context Engine

    Agentic Context Engine

    Make your agents learn from experience

    Agentic Context Engine (ACE) is an open-source framework designed to help AI agents improve their performance by learning from their own execution history. Instead of relying solely on model training or fine-tuning, the framework focuses on structured context engineering, allowing agents to accumulate knowledge from past successes and failures during task execution. The system treats context as a dynamic “playbook” that evolves over time through a process of generation, reflection, and curation, enabling agents to refine strategies across repeated tasks. ...
    Downloads: 0 This Week
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  • 25
    Synthetic Data Generator

    Synthetic Data Generator

    SDG is a specialized framework

    Synthetic Data Generator is an open-source framework designed to generate high-quality synthetic tabular datasets that replicate the statistical characteristics of real data while avoiding privacy risks. The platform enables developers and data scientists to create artificial datasets that preserve important relationships between variables without containing sensitive personal information.
    Downloads: 0 This Week
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