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Showing 25 open source projects for "fifa 12 mac"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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12-Factor Agents
What are the principles we can use to build LLM-powered software
12-Factor Agents is a conceptual engineering guide that defines a set of principles for building reliable, scalable, and maintainable LLM-powered applications. Inspired by the original Twelve-Factor App methodology, the project reframes best practices specifically for agentic systems and AI software. It outlines patterns such as treating prompts as first-class assets, owning the context window, and converting natural language into structured tool calls. The repository emphasizes operational... -
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Artificial Intelligence for Beginners
12 Weeks, 24 Lessons, AI for All
AI-For-Beginners is a comprehensive open-source educational curriculum designed to introduce learners to the foundations of artificial intelligence through structured lessons and hands-on practice. The repository provides a 12-week program composed of 24 lessons that combine theory, code examples, quizzes, and laboratory exercises. It covers a broad range of topics including neural networks, computer vision, natural language processing, and AI ethics. The curriculum is intentionally... -
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SkyPilot
SkyPilot: Run AI and batch jobs on any infra
SkyPilot is a framework for running AI and batch workloads on any infra, offering unified execution, high cost savings, and high GPU availability. Run AI and batch jobs on any infra (Kubernetes or 12+ clouds). Get unified execution, cost savings, and high GPU availability via a simple interface. -
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GLM-4.5
GLM-4.5: Open-source LLM for intelligent agents by Z.ai
GLM-4.5 is a cutting-edge open-source large language model designed by Z.ai for intelligent agent applications. The flagship GLM-4.5 model has 355 billion total parameters with 32 billion active parameters, while the compact GLM-4.5-Air version offers 106 billion total parameters and 12 billion active parameters. Both models unify reasoning, coding, and intelligent agent capabilities, providing two modes: a thinking mode for complex reasoning and tool usage, and a non-thinking mode for... -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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GluonTS
Probabilistic time series modeling in Python
GluonTS is a Python package for probabilistic time series modeling, focusing on deep learning based models. GluonTS requires Python 3.6 or newer, and the easiest way to install it is via pip. We train a DeepAR-model and make predictions using the simple "airpassengers" dataset. The dataset consists of a single time-series, containing monthly international passengers between the years 1949 and 1960, a total of 144 values (12 years * 12 months). We split the dataset into train and test parts,... -
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MARS5
MARS5 speech model (TTS) from CAMB.AI
MARS5-TTS is CAMB.AI’s open-source English speech model designed for high-quality text-to-speech and voice emulation. It uses a two-stage architecture that combines an autoregressive (AR) model with a non-autoregressive (NAR) model, giving it both expressiveness and speed. The model is built to handle prosodically challenging content such as sports commentary, anime dialogue, and other high-energy or highly varied speech patterns with realistic rhythm and intonation. To control speaker... -
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NeuroMatch Academy (NMA)
NMA Computational Neuroscience course
NMA Computational Neuroscience course. We have curated a curriculum that spans most areas of computational neuroscience (a hard task in an increasingly big field!). We will expose you to both theoretical modeling and more data-driven analyses. The Neuro Video Series is a series of 12 videos that covers basic neuroscience concepts and neuroscience methods. These videos are completely optional and do not need to be watched in a fixed order so you can pick and choose which videos will help you... -
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Claude-Flow
The leading agent orchestration platform for Claude
Claude-Flow v2 Alpha is an advanced AI orchestration and automation framework designed for enterprise-grade, large-scale AI-driven development. It enables developers to coordinate multiple specialized AI agents in real time through a hive-mind architecture, combining swarm intelligence, neural reasoning, and a powerful set of 87 Modular Control Protocol (MCP) tools. The platform supports both quick swarm tasks and persistent multi-agent sessions known as hives, facilitating distributed AI... -
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Best-of Machine Learning with Python
A ranked list of awesome machine learning Python libraries
This curated list contains 900 awesome open-source projects with a total of 3.3M stars grouped into 34 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an issue, submit a pull request, or directly edit the projects.yaml. Contributions are very welcome! General-purpose machine learning and deep learning... -
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tf2onnx
Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
tf2onnx converts TensorFlow (tf-1.x or tf-2.x), keras, tensorflow.js and tflite models to ONNX via command line or python API. Note: tensorflow.js support was just added. While we tested it with many tfjs models from tfhub, it should be considered experimental. TensorFlow has many more ops than ONNX and occasionally mapping a model to ONNX creates issues. tf2onnx will use the ONNX version installed on your system and installs the latest ONNX version if none is found. We support and test ONNX... -
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Translate-Subtitle-File
Subtitle Creation Assistant
Subtitle group machine translation assistant - [Function 1: Translate subtitle file] .srt .ass .vtt [Function 2: Voice to text] (Drag in video or audio to recognize subtitles) (The latest version v4.1.0 Update time 2021 2 May 23) 12 translation service providers can be configured, such as Google, Baidu, Tencent, Caiyun, IBM, Azure, Amazon, etc. (6 voice service providers can be configured: Alibaba Cloud, Xunfei, Tencent Cloud, IBM, Azure, Amazon ) Advantages: 1. You can use multiple service... -
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Audiomentations
A Python library for audio data augmentation
A Python library for audio data augmentation. Inspired by albumentations. Useful for deep learning. Runs on CPU. Supports mono audio and multichannel audio. Can be integrated in training pipelines in e.g. Tensorflow/Keras or Pytorch. Has helped people get world-class results in Kaggle competitions. Is used by companies making next-generation audio products. Mix in another sound, e.g. a background noise. Useful if your original sound is clean and you want to simulate an environment where... -
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WhisperSpeech
An Open Source text-to-speech system built by inverting Whisper
WhisperSpeech is an open-source text-to-speech system created by “inverting” OpenAI’s Whisper, reusing its strengths as a semantic audio model to generate speech instead of only transcribing it. The project aims to be for speech what Stable Diffusion is for images: powerful, hackable, and safe for commercial use, with code under Apache-2.0/MIT and models trained only on properly licensed data. Its architecture follows a token-based, multi-stage pipeline inspired by AudioLM and SPEAR-TTS:... -
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FLUX.1 Krea
Powerful open source image generation model
FLUX.1 Krea [dev] is an open-source 12-billion parameter image generation model developed collaboratively by Krea and Black Forest Labs, designed to deliver superior aesthetic control and high image quality. It is a rectified-flow model distilled from the original Krea 1, providing enhanced sampling efficiency through classifier-free guidance distillation. The model supports generation at resolutions between 1024 and 1280 pixels with recommended inference steps between 28 and 32 for optimal... -
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Dead Deer 3.14.82.2025
3D modeler, 3D game maker, 3D demo maker
3D modeler, 3D game maker, 3D demo maker. to model and create games, demos. Scripting language allows you to code interactions in pseudo-C with the animation and synthesize your own rendering with own-made shaders. Import FBX, BLEND, GLTF, OBJ, 3DS, DAE, X, XML, STL, PCB, ASC, PLY, GSPLATS. Cross-platform project WINDOWS 32/64 /MACOSX 10.6/ 10.8+/APPLSilicon /LINUX/iOS/ANDROID/WINDOWS PHONE/GOOGLE VR/OPEN VR/OCULUS VR/WEBASM/UWP8/10/OPENXR, PIs (ARM32/64), RISCV Players and... -
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MyBox
Easy Tools of PDF, Image, File, Network, Data, and Medias
javafx-desktop-apps pdf image ocr icc barcode color-palette text bytes markdown html archive compress digest video audio editor converter media https://github.com/Mararsh/MyBox Self-contain packages need not java env nor installation. Jar packages need Java 16 or higher. -
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MetaTransformer
Meta-Transformer for Unified Multimodal Learning
We're thrilled to present OneLLM, an ensembling Meta-Transformer framework with Multimodal Large Language Models, which performs multimodal joint training, supports more modalities including fMRI, Depth, and Normal Maps, and demonstrates very impressive performances on 25 benchmarks. -
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Learn_Data_Science_in_3_Months
This is the Curriculum for "Learn Data Science in 3 Months"
This project lays out a 12-week plan to go from basics to a portfolio-ready understanding of data science. It breaks the journey into clear stages: Python fundamentals, data wrangling, visualization, statistics, machine learning, and end-to-end projects. The schedule mixes learning and doing, encouraging you to build small deliverables each week—like notebooks, dashboards, and model demos—to reinforce skills. It also includes suggestions for datasets and problem domains so you aren’t stuck... -
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Devanagari OCR
Devanagari Optical Character Recognition, Annotation tool
The project has source code and data related to the following tools: 1. Optical Character Recognition. Recognize machine printed Devanagari with or without a dictionary. 2. Document Image Analysis. Automatic page segmentation of document images in multiple Indian languages. Identifies pictures, lines, and words in a document scanned at 300 dpi. 3. Multi-lingual annotation. An interface that has transilteration and a soft-keyboard using which multiple languages can be input.... -
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LWPR
Locally Weighted Projection Regression (LWPR)
Locally Weighted Projection Regression (LWPR) is a fully incremental, online algorithm for non-linear function approximation in high dimensional spaces, capable of handling redundant and irrelevant input dimensions. At its core, it uses locally linear models, spanned by a small number of univariate regressions in selected directions in input space. A locally weighted variant of Partial Least Squares (PLS) is employed for doing the dimensionality reduction. Please cite: [1] Sethu... -
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IMPORTANT UPDATE! This project has migrated to https://github.com/polyworld/polyworld . This SourceForge repository is now obsolete. Polyworld is one of the earliest and most sophisticated artificial worlds developed to study Artificial Life and Artificial Intelligence, using computational genetics, physiology, metabolism, neural networks, learning, vision, and behavior.
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GLM-4.5-Air
Compact hybrid reasoning language model for intelligent responses
GLM-4.5-Air is a multilingual large language model with 106 billion total parameters and 12 billion active parameters, designed for conversational AI and intelligent agents. It is part of the GLM-4.5 family developed by Zhipu AI, offering hybrid reasoning capabilities via two modes: a thinking mode for complex reasoning and tool use, and a non-thinking mode for immediate responses. The model is optimized for efficiency and deployment, delivering strong results across 12 industry benchmarks,... -
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layoutlm-base-uncased
Multimodal Transformer for document image understanding and layout
layoutlm-base-uncased is a multimodal transformer model developed by Microsoft for document image understanding tasks. It incorporates both text and layout (position) features to effectively process structured documents like forms, invoices, and receipts. This base version has 113 million parameters and is pre-trained on 11 million documents from the IIT-CDIP dataset. LayoutLM enables better performance in tasks where the spatial arrangement of text plays a crucial role. The model uses a... -
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roberta-base
Robust BERT-based model for English with improved MLM training
roberta-base is a robustly optimized variant of BERT, pretrained on a significantly larger corpus of English text using dynamic masked language modeling. Developed by Facebook AI, RoBERTa improves on BERT by removing the Next Sentence Prediction objective, using longer training, larger batches, and more data, including BookCorpus, English Wikipedia, CC-News, OpenWebText, and Stories. It captures contextual representations of language by masking 15% of input tokens and predicting them.... -
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FLUX.1-Krea-dev
Text-to-image model optimized for artistic quality and safe generation
FLUX.1-Krea-dev is a 12 billion parameter rectified flow transformer for text-to-image generation, developed by Black Forest Labs in collaboration with Krea. It delivers aesthetic, high-quality outputs focused on photography and visual coherence, making it a strong competitor to closed-source models. Trained using guidance distillation, it offers efficient inference while preserving creative fidelity. The model is distributed under a non-commercial license, with conditions to prevent misuse...
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