Search Results for "setup-subversion-1.7.8.exe"
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Showing 136 open source projects for "setup-subversion-1.7.8.exe"
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1
GPT Computer Assistant
gpt-4o for windows, macos and linux
...In this way, this is a fresh and stable work. You can easily install as a Python library for this time but we will prepare a pipeline for providing native install scripts (.exe). -
2
Fooocus
Focus on prompting and generating
...Built on Gradio and leveraging Stable Diffusion XL, Fooocus eliminates the need for manual parameter tweaking, allowing users to focus solely on crafting prompts. It offers a user-friendly interface with minimal setup, making advanced image synthesis accessible to a broader audience. -
3
Stable Diffusion WebUI Docker
Easy Docker setup for Stable Diffusion with user-friendly UI
Stable Diffusion WebUI Docker is a Docker-based repository that simplifies running Stable Diffusion with rich user interfaces by packaging multiple popular web UIs into an easy-to-deploy containerized solution. It integrates leading community UIs like AUTOMATIC1111 and ComfyUI into a Docker Compose setup that can be started with a single command, abstracting away dependency installation and environment configuration. Users can choose which UI profile they want to run — for example, full feature AUTOMATIC1111, CPU-only automatic builds, or ComfyUI workflows — and launch them in a consistent, isolated container environment with automatic model and data caching. ... -
4
Bear Stone Smart Home
Custom Home Assistant configuration with automations and scripts setup
...Additionally, it may include examples of dashboards and user interface customization to enhance usability and visualization of home data. Overall, it serves as a practical reference for building and refining a tailored Home Assistant setup. -
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5
Harbor LLM
Run a full local LLM stack with one command using Docker
...It is intended for local development and experimentation rather than production deployment, giving developers a flexible way to explore AI systems, test configurations, and manage complex LLM stacks without manual wiring or setup overhead. -
6
firerpa LAMDA
The most powerful Android RPA agent framework
...It exposes a clean UI to monitor and interact with connected devices and includes tooling to script actions reliably across apps and OS versions. The project emphasizes low-friction setup and powerful control primitives so teams can move from interactive validation to repeatable automation. A public wiki, releases, and issue tracker show active development across areas like connectivity, instrumentation compatibility, and robustness under detection. Together with companion projects (e.g., a device hub), lamda is positioned as a next-generation mobile automation stack rather than a single tool. ... -
7
OpenOutreach
Linkedin Automation Tool
...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. -
8
GPT4Free
The official gpt4free repository
gpt4free is an open-source project offering free, unrestricted access to GPT‑4–style language models without requiring an API key. The repository includes scripts and server implementations designed to replicate OpenAI’s GPT‑4 API behavior by leveraging publicly available or self-hosted models. It’s licensed under GPL‑v3. -
9
LLaMA-Factory
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
LLaMA-Factory is a fine-tuning and training framework for Meta's LLaMA language models. It enables researchers and developers to train and customize LLaMA models efficiently using advanced optimization techniques. -
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10
kokoro-onnx
TTS with kokoro and onnx runtime
kokoro-onnx is a text-to-speech toolkit that wraps the Kokoro neural TTS model in an easy-to-use ONNX Runtime interface, so you can generate speech from Python with minimal setup. It focuses on running efficiently on commodity hardware, including macOS with Apple Silicon, while still delivering near real-time performance for many use cases. The project ships prebuilt model files and a simple example script, so you can go from installation to producing an audio.wav file in just a few steps. It supports multiple languages and voices, with a curated voice list and configuration via a VOICES file hosted alongside the models. ... -
11
DINOv3
Reference PyTorch implementation and models for DINOv3
DINOv3 is the third-generation iteration of Meta’s self-supervised visual representation learning framework, building upon the ideas from DINO and DINOv2. It continues the paradigm of learning strong image representations without labels using teacher–student distillation, but introduces a simplified and more scalable training recipe that performs well across datasets and architectures. DINOv3 removes the need for complex augmentations or momentum encoders, streamlining the pipeline while... -
12
mcpo
A simple, secure MCP-to-OpenAPI proxy server
...This design lets you reuse a growing library of MCP servers with platforms that only understand HTTP+OpenAPI, unifying tool access across ecosystems. The project emphasizes “dead-simple” setup and pairs with Open WebUI documentation that shows end-to-end integration. It supports running multiple tools and makes them discoverable to clients that expect Swagger/JSON schemas. In practice, mcpo shortens the path from a local MCP tool to a shareable, network-accessible microservice. -
13
FLUX.1
Official inference repo for FLUX.1 models
FLUX.1 repository contains inference code and tooling for the FLUX.1 text-to-image diffusion models, enabling developers and researchers to generate and edit images from natural-language prompts using open-weight versions of the model on their own hardware or within custom applications. The project is part of a larger family of FLUX models developed by Black Forest Labs, designed to produce high-quality, detailed visuals from text descriptions with competitive prompt adherence and artistic... -
14
self-llm
Tutorial tailored for Chinese babies on rapid fine-tuning
...The repository focuses on helping beginners and developers understand how to run and customize modern LLMs locally rather than relying solely on hosted APIs. It provides step-by-step tutorials covering environment setup, model deployment, inference workflows, and efficient fine-tuning techniques such as LoRA and parameter-efficient training. The project also includes guides for integrating models into real applications, including command-line interfaces, web demos, and frameworks like LangChain. By combining theory, configuration instructions, and runnable examples, self-llm lowers the barrier to entry for students and engineers who want to experiment with open-source models. -
15
ticket
Fast, powerful, git-native ticket tracking in a single bash script
ticket is a lightweight, git-native ticket management tool implemented as a single Bash script that brings powerful issue tracking directly into your Git workflows without requiring a database or complex setup. It stores each ticket as a Markdown file with YAML frontmatter, making them human-readable and easy to version control alongside your code, while also allowing IDEs to jump straight to ticket definitions. The CLI provides common subcommands to create, list, edit, close, and manage dependencies between tickets, enabling clear hierarchical task structures and visual dependency trees. ... -
16
Self-hosted AI Package
Run all your local AI together in one package
...The stack typically includes Ollama for running local large language models, n8n as a low-code workflow automation platform, Supabase for database and vector storage, Open WebUI for interacting with models, Flowise for agent building, and additional services like SearXNG, Neo4j, and Langfuse for search, knowledge graphs, and observability. This integrated setup allows users to experiment with RAG pipelines, automated workflows, AI agents, and project data management without relying on external hosted services, increasing flexibility and privacy. The repository comes with example workflows (such as Local RAG AI Agent workflows) and environment configurations that help streamline setup and encourage customization. -
17
Courses (Anthropic)
Anthropic's educational courses
...Assignments emphasize realistic tasks such as building small utilities, testing prompts against edge cases, and measuring quality so you learn to ship things that work. The materials are written for developers but remain friendly to newcomers, with clear setup instructions and minimal boilerplate. Because the repo is live and maintained, lessons are updated as the SDK and models evolve, and issues are used to track fixes, clarifications, and new modules. -
18
Chandra
OCR model for complex documents with layout-aware structured outputs
...It is capable of handling over 40 languages and is optimized to read difficult inputs such as messy handwriting and multi-column layouts. Chandra can be run locally using transformer-based inference or deployed with a high-performance server setup for large-scale processing. It also includes command-line tools and optional web-based interfaces to simplify interaction and batch processing workflows. -
19
MCP Atlassian
MCP server that integrates Confluence and Jira
The MCP Atlassian server integrates Atlassian products like Confluence and Jira with the Model Context Protocol. It supports both Cloud and Server/Data Center deployments, enabling AI models to interact with these platforms securely. -
20
DeepSeek-V3.2-Exp
An experimental version of DeepSeek model
...The key innovation in this version is DeepSeek Sparse Attention (DSA), a sparse attention mechanism that aims to optimize training and inference efficiency in long-context settings without degrading output quality. According to the authors, they aligned the training setup of V3.2-Exp with V3.1-Terminus so that benchmark results remain largely comparable, even though the internal attention mechanism changes. In public evaluations across a variety of reasoning, code, and question-answering benchmarks (e.g. MMLU, LiveCodeBench, AIME, Codeforces, etc.), V3.2-Exp shows performance very close to or in some cases matching that of V3.1-Terminus. ... -
21
Get Physics Done (GPD)
The first open-source agentic AI physicist
Get Physics Done (GPD) is an open-source project designed to accelerate scientific research in physics by leveraging modern computational tools and automation techniques. It aims to simplify the process of performing simulations, calculations, and experimental analysis by providing structured workflows that integrate computational physics methods with reproducible research practices. The project focuses on reducing the friction involved in setting up experiments, running simulations, and... -
22
SD.Next
All-in-one WebUI for AI generative image and video creation
...It is designed as a power-user environment where model management, generation features, and workflow controls are centralized in a single UI rather than spread across separate scripts and utilities. The project emphasizes broad model support and includes mechanisms for discovering, downloading, and configuring models through integrated tooling, lowering the setup burden for experimentation. It also provides documentation and an ecosystem of guides that help users move from basic generation to more advanced usage patterns, including API-based automation. SD.Next is built to run across common desktop platforms and focuses on practicality: install, generate, iterate, and automate with minimal friction. -
23
autoresearch
AI agents autonomously run and improve ML experiments overnight
autoresearch is an experimental framework that enables AI agents to autonomously conduct machine learning research by iteratively modifying and training models. Created by Andrej Karpathy, the project allows an agent to edit the model training code, run short experiments, evaluate results, and repeat the process without human intervention. Each experiment runs for a fixed five-minute training window, enabling rapid iteration and consistent comparison across architectural or hyperparameter... -
24
Stable Diffusion web UI for AMDGPUs
Stable Diffusion WebUI optimized for AMD GPUs with editing tools
...It includes tools such as inpainting and outpainting for editing specific areas of an image, along with features like prompt matrix generation and attention controls to fine-tune outputs. Users can emphasize or de-emphasize elements in prompts to influence results more precisely. A one-click setup script simplifies installation, although Python and Git are still required. Stable Diffusion WebUI AMDGPU focuses on improving accessibility for AMD GPU users, offering an alternative to CUDA-based implementations while maintaining compatibility with many existing Stable Diffusion capabilities and extensions. -
25
autoresearch
AI agents running research on single-GPU nanochat training
Autoresearch is an experimental AI-driven research framework that automates the process of training and improving machine learning models by allowing autonomous agents to iteratively modify and evaluate code. The system is built around the idea of giving an AI agent control over a simplified training pipeline, where it can experiment with model architectures, hyperparameters, and optimization strategies without direct human intervention. It operates within a constrained environment using a...
