Showing 2758 open source projects for "compiler python linux"

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  • 1
    Phi-3-MLX

    Phi-3-MLX

    Phi-3.5 for Mac: Locally-run Vision and Language Models

    Phi-3-Vision-MLX is an Apple MLX (machine learning on Apple silicon) implementation of Phi-3 Vision, a lightweight multi-modal model designed for vision and language tasks. It focuses on running vision-language AI efficiently on Apple hardware like M1 and M2 chips.
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  • 2
    Open Autonomy

    Open Autonomy

    A framework for the creation of autonomous agent services

    Open Autonomy is a framework that enables the development of autonomous economic agents (AEAs) capable of operating independently in various economic contexts.
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  • 3
    Adapters

    Adapters

    A Unified Library for Parameter-Efficient Learning

    Adapters is an add-on library to HuggingFace's Transformers, integrating 10+ adapter methods into 20+ state-of-the-art Transformer models with minimal coding overhead for training and inference. Adapters provide a unified interface for efficient fine-tuning and modular transfer learning, supporting a myriad of features like full-precision or quantized training (e.g. Q-LoRA, Q-Bottleneck Adapters, or Q-PrefixTuning), adapter merging via task arithmetics or the composition of multiple adapters...
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  • 4
    Llama Recipes

    Llama Recipes

    Scripts for fine-tuning Meta Llama3 with composable FSDP & PEFT method

    The 'llama-recipes' repository is a companion to the Meta Llama models. We support the latest version, Llama 3.1, in this repository. The goal is to provide a scalable library for fine-tuning Meta Llama models, along with some example scripts and notebooks to quickly get started with using the models in a variety of use-cases, including fine-tuning for domain adaptation and building LLM-based applications with Llama and other tools in the LLM ecosystem. The examples here showcase how to run...
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  • 5
    spacy-llm

    spacy-llm

    Integrating LLMs into structured NLP pipelines

    Large Language Models (LLMs) feature powerful natural language understanding capabilities. With only a few (and sometimes no) examples, an LLM can be prompted to perform custom NLP tasks such as text categorization, named entity recognition, coreference resolution, information extraction and more. This package integrates Large Language Models (LLMs) into spaCy, featuring a modular system for fast prototyping and prompting, and turning unstructured responses into robust outputs for various...
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  • 6
    runprompt

    runprompt

    Run LLM prompts from your shell

    runprompt is an interactive command launcher and prompt utility that lets users bind shell commands, scripts, and workflows to quick keyboard shortcuts or natural-language queries, helping streamline repetitive terminal tasks and boost developer productivity. It functions as a lightweight, launcher-centric interface where you can type a phrase, partial command, or alias and have RunPrompt suggest or execute relevant actions instantly, reducing the need to memorize long commands or navigate...
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  • 7
    GLM-4.5V

    GLM-4.5V

    GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning

    GLM-4.5V is the preceding iteration in the GLM-V series that laid much of the groundwork for general multimodal reasoning and vision-language understanding. It embodies the design philosophy of mixing visual and textual modalities into a unified model capable of general-purpose reasoning, content understanding, and generation, while already supporting a wide variety of tasks: from image captioning and visual question answering to content recognition, GUI-based agents, video understanding,...
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  • 8
    AI Infra

    AI Infra

    Understanding of AI Infra: Quantitative Analysis and System Design

    AI Infra Book is an open-source technical book and companion repository focused on the infrastructure behind modern large language models. It approaches inference and training through quantitative analysis of hardware limits, data movement, model architecture, and distributed systems. The book contains twelve chapters supported by formulas, diagrams, experiments, and case studies. Companion tools help readers reproduce resource calculations and inspect the assumptions behind system-design...
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  • 9
    MSA: Memory Sparse Attention

    MSA: Memory Sparse Attention

    Trainable latent-memory framework for 100M-token contexts

    MSA, or Memory Sparse Attention, is a research framework for scaling language-model memory to extremely long contexts. It replaces full attention over all tokens with sparse selection of compressed latent memory states. Document-wise rotary position encoding and top-k routing keep training and inference close to linear complexity. A tiered KV-cache design stores routing keys on GPU while larger content states can remain on CPU. Its Memory Parallel engine distributes scoring and transfers...
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  • 10
    NeMo Automodel

    NeMo Automodel

    Pytorch Distributed native training library for LLMs/VLMs

    NeMo AutoModel is NVIDIA's open-source PyTorch Distributed training library for scaling LLM, VLM, diffusion, and retrieval-model training. Its DTensor-native SPMD approach lets the same training code scale from one GPU to large multi-node clusters by changing configuration. Hugging Face integration provides broad model compatibility without requiring format conversion. YAML recipes and CLI overrides keep experiments concise while preserving reproducibility. The library supports composable...
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  • 11
    Semantica

    Semantica

    Graph-Native Infrastructure for Context and Accountable AI Systems

    Semantica is an open-source graph-native infrastructure layer for building explainable and auditable AI systems. It ingests fragmented data, extracts meaningful entities and relationships, and transforms them into context and knowledge graphs. Deterministic reasoning, ontology management, provenance tracking, and decision records help explain how conclusions were reached. The platform can complement existing LLMs, vector databases, and agent frameworks rather than replacing them. It supports...
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  • 12
    MCP Agent Mail

    MCP Agent Mail

    Asynchronous coordination layer for AI coding agents

    MCP Agent Mail is an asynchronous coordination service for teams of AI coding agents working on the same software. It gives each agent a persistent identity, inbox, outbox, searchable history, and threaded Markdown conversations. Agents can send decisions, status updates, images, and attachments without relying on a human to relay context between parallel sessions. Advisory file reservations let an agent declare intended edits to files or patterns, reducing accidental overlap without...
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  • 13
    Harness Engineering

    Harness Engineering

    Field guide, and agent context bundle for harness engineering

    Harness Engineering is a retrieval-optimized anthology, field guide, and agent context bundle for improving AI coding-agent performance. It treats the model and agent as fixed while strengthening the surrounding context, tools, constraints, and proof mechanisms. The repository organizes developed arguments, practical cases, source evidence, evaluations, and reusable playbooks into distinct layers. Its agent guide routes each task to the smallest relevant set of materials instead of loading...
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  • 14
    Three.js Object Sculptor

    Three.js Object Sculptor

    Codex plugin that turns attached object images into code-only

    Three.js Object Sculptor is a Codex plugin that converts a reference image into a procedural Three.js object written entirely in code. It first evaluates whether the image is suitable and produces an ObjectSculptSpec describing geometry, materials, lighting, hierarchy, pivots, and quality targets. Codex then follows staged passes from blockout and structural work through surface detail, interaction design, and optimization. Generated models include meaningful sockets and anchors for...
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  • 15
    Boogu-Image-0.1

    Boogu-Image-0.1

    Apache-2.0 open-source image generation and editing model family

    Boogu-Image is an open-source image generation and editing model family focused on unified multimodal understanding and generation. It includes Base, Turbo, Edit, and Edit-Turbo variants for different speed and quality needs. The project supports text-to-image generation, image-to-image editing, fast distilled inference, and Chinese-English text rendering. It is designed to handle photography, posters, products, stylized art, dense text layouts, and precise in-image text edits. The...
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  • 16
    zhengxi-views

    zhengxi-views

    Zheng Xi (Efonda Fund Manager) Investment Research Agent Skill

    zhengxi-views is a traceable investment research Agent Skill centered on the public views of Zheng Xi, a fund manager at E Fund. It is built to reduce unsupported AI answers by grounding responses in original public statements, fund reports, interviews, and documented methodology. The project organizes a corpus of Zheng Xi’s views from 2012 to 2026, then connects those materials to an extracted investment framework. It also includes real fund data snapshots for managed funds and broader fund...
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  • 17
    Local-NotebookLM

    Local-NotebookLM

    Googles NotebookLM but local

    Local-NotebookLM is a local AI tool for turning PDF documents into generated audio content. It works like a self-hosted alternative to NotebookLM-style document-to-audio workflows. The system extracts and processes PDF text, sends the content through an LLM, and converts the result into speech with configurable voices. Users can generate podcasts, summaries, interviews, lectures, debates, tutorials, news reports, executive briefs, and other formats. It supports multiple LLM providers,...
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  • 18
    Hy-MT2
    Hy-MT2 is a family of fast-thinking multilingual translation models built for complex real-world translation scenarios. It includes 1.8B, 7B, and 30B-A3B model sizes, giving users options for lightweight deployment, stronger general performance, or MoE-based capacity. The models support translation across 33 languages and are designed to follow detailed translation instructions in multiple languages. They can handle tasks involving terminology, style, personalization, delimiters, structured...
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  • 19
    Hiring Agent

    Hiring Agent

    AI agent to evaluate and score resumes

    Hiring Agent is an AI-powered resume evaluation pipeline for screening technical candidates. It reads a resume PDF and converts the content into Markdown-like text. It then uses a local or hosted language model to extract structured candidate information into sectioned JSON. The system can enrich that resume data with GitHub profile and repository signals when a profile is available. After the data is collected, it produces an explainable evaluation with category scores, supporting evidence,...
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  • 20
    PixelRAG

    PixelRAG

    The beginning of scalable pixel-native search

    PixelRAG is a visual retrieval-augmented generation system that searches documents by how they look, not only by the text they contain. It renders web pages, PDFs, and images into screenshot tiles, then performs retrieval over those visual representations. This approach preserves layout, tables, charts, diagrams, infographics, and other visual structure that traditional HTML or text parsing can miss. The project includes tools for rendering, chunking, embedding, indexing, and serving visual...
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  • 21
    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,...
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  • 22
    Dia2

    Dia2

    TTS model capable of streaming conversational audio in realtime

    Dia2 is a streaming dialogue text-to-speech model created by Nari Labs for generating conversational audio in real time. It is designed to begin producing speech before receiving the entire input text, which makes it useful for interactive voice applications. The model supports audio conditioning, allowing generated speech to follow a reference voice or conversational style more naturally. Dia2 provides 1B and 2B model checkpoints along with inference code for research and experimentation....
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  • 23
    SkillOpt

    SkillOpt

    Text-space optimizer that trains reusable natural-language skills

    SkillOpt is a Microsoft research project for improving frozen LLM agents by optimizing reusable natural-language skill documents. Instead of changing model weights, it treats a compact skill file as the trainable state of the agent. The system learns from agent rollouts, reflection, bounded edits, and validation gates to produce better instructions over time. Its output is a deployable best_skill.md artifact that can be reused across agent tasks. The project is focused on making agents more...
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  • 24
    Train LLM From Scratch

    Train LLM From Scratch

    A straightforward method for training your LLM

    Train LLM From Scratch is an educational PyTorch project that shows how to build and train a transformer-based language model from the ground up. It is based on the architecture described in Attention Is All You Need and is designed to make the training pipeline understandable rather than hidden behind a large framework. The repository walks through the process from downloading data to generating text with a trained model. It supports training smaller or larger models, including million- and...
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  • 25
    Agent Control

    Agent Control

    Centralized agent control plane for governing runtime agent behavior

    Agent Control is a centralized control plane for governing AI agent behavior at runtime across different frameworks and deployment environments. It lets teams define controls once and apply them consistently to agents without rewriting the agent’s core code. The platform evaluates agent inputs and outputs against configurable policies to reduce risks such as prompt injection, unsafe responses, sensitive data exposure, and policy drift. It is designed for production environments where...
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