Search Results for "git:/git.code.sf.net/p/docfetcher/code" - Page 43
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Showing 1508 open source projects for "git:/git.code.sf.net/p/docfetcher/code"
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1
ConvNeXt V2
Code release for ConvNeXt V2 model
...The result is a convnet that competes strongly with transformer architectures on recognition benchmarks while being efficient and hardware-friendly. The repository provides official PyTorch implementations for multiple model sizes (Atto, Femto, Pico, up through Huge), conversion from JAX weights, code for pretraining/fine-tuning, and pretrained checkpoints. It supports both self-supervised pretraining and supervised fine-tuning. -
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minGPT
A minimal PyTorch re-implementation of the OpenAI GPT
minGPT is a minimalist, educational re-implementation of the GPT (Generative Pretrained Transformer) architecture built in PyTorch, designed by Andrej Karpathy to expose the core structure of a transformer-based language model in as few lines of code as possible. It strips away extraneous bells and whistles, aiming to show how a sequence of token indices is fed into a stack of transformer blocks and then decoded into the next token probabilities, with both training and inference supported. Because the whole model is around 300 lines of code, users can follow each step—from embedding lookup, positional encodings, multi-head attention, feed-forward layers, to output heads—and thus demystify how GPT-style models work beneath the surface. ... -
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DeepMozart
Audio generation using diffusion models
Audio generation using diffusion models in PyTorch. The code is based on the audio-diffusion-pytorch repository. -
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Mars Framework
Mars is a tensor-based unified framework for large-scale data
...The project provides a tensor-based execution model that extends the capabilities of tools such as NumPy, pandas, and scikit-learn so that large datasets can be processed in parallel without rewriting code for distributed environments. Its architecture automatically divides large computational tasks into smaller chunks that can be executed across multiple nodes in a cluster, allowing complex analytics, machine learning workflows, and data transformations to run efficiently at scale. Mars is particularly useful for workloads that exceed the memory capacity of a single machine or require high levels of parallel processing. -
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Multi-Agent Particle Envs
Code for a multi-agent particle environment used in a paper
...Scenarios are designed to model cooperative, competitive, and mixed interactions among agents, making it useful for testing algorithms in multi-agent settings. The project includes built-in scenarios such as navigation to landmarks, cooperative tasks, and adversarial setups. Although archived, its concepts and code structure remain foundational for more advanced libraries like PettingZoo, which extended and maintained this environment. -
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Machine Learning Git Codebook
For extensive instructor led learning
Machine Learning Git Codebook is an educational repository that provides a structured introduction to data science and machine learning concepts through a series of interactive notebooks and practical examples. The project is designed as a self-paced learning resource that walks learners through the full data science workflow, including data preprocessing, exploratory analysis, feature engineering, and model development. -
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Mintlify Writer
AI powered documentation writer
Writing documentation sucks. Let Mintlify take care of it. Just highlight code and see the magic. -
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CPT
CPT: A Pre-Trained Unbalanced Transformer
A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Generation. We replace the old BERT vocabulary with a larger one of size 51271 built from the training data, in which we 1) add missing 6800+ Chinese characters (most of them are traditional Chinese characters); 2) remove redundant tokens (e.g. Chinese character tokens with ## prefix); 3) add some English tokens to reduce OOV. Position Embeddings We extend the max_position_embeddings from 512 to 1024. We... -
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UnionML
Build and deploy machine learning microservices
...Data science, ML engineering, and MLOps practitioners can all gather around UnionML apps as a way of defining a single source of truth about your ML system’s behavior. This helps you maintain consistent code across your ML stack, from training to prediction logic. -
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d2l-zh
Chinese-language edition of Dive into Deep Learning
d2l‑zh is the Chinese-language edition of Dive into Deep Learning, an interactive, open‑source deep learning textbook that combines code, math, and explanatory text. It features runnable Jupyter notebooks compatible with multiple frameworks (e.g., PyTorch, MXNet, TensorFlow), comprehensive theoretical analysis, and exercises. Widely adopted in over 70 countries and used by more than 500 universities for teaching deep learning. -
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MTCNN Face Detection Alignment
Joint Face Detection and Alignment
MTCNN_face_detection_alignment is an implementation of the “Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks” algorithm. The algorithm uses a cascade of three convolutional networks (P-Net, R-Net, O-Net) to jointly detect faces (bounding boxes) and align facial landmarks in a coarse-to-fine manner, leveraging multi-task learning. Non-maximum suppression and bounding box regression at each stage. The repository includes Caffe / MATLAB code, support scripts, and instructions for dependencies. Non-maximum suppression and bounding box regression at each stage. ... -
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CleanRL
High-quality single file implementation of Deep Reinforcement Learning
...The implementation is clean and simple, yet we can scale it to run thousands of experiments using AWS Batch. CleanRL is not a modular library and therefore it is not meant to be imported. At the cost of duplicate code, we make all implementation details of a DRL algorithm variant easy to understand, so CleanRL comes with its own pros and cons. You should consider using CleanRL if you want to 1) understand all implementation details of an algorithm's variant or 2) prototype advanced features that other modular DRL libraries do not support (CleanRL has minimal lines of code so it gives you great debugging experience and you don't have to do a lot of subclassing like sometimes in modular DRL libraries). -
13
PerlPP
Perl preprocessor - embed Perl source in any file
...The following commands work mostly analogously to their C preprocessor counterparts. but $fn can be determined programmatically. Note that defines set with -D or -s do not take effect until after the script has been generated, which is after the macro code runs. -
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Minimal text diffusion
A minimal implementation of diffusion models for text generation
A minimal implementation of diffusion models of text: learns a diffusion model of a given text corpus, allowing to generate text samples from the learned model. The main idea was to retain just enough code to allow training a simple diffusion model and generating samples, remove image-related terms, and make it easier to use. To train a model, run scripts/train.sh. By default, this will train a model on the simple corpus. However, you can change this to any text file using the --train_data argument. Note that you may have to increase the sequence length (--seq_len) if your corpus is longer than the simple corpus. ... -
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learn-machine-learning-in-two-months
Essential Knowledge for learning Machine Learning in two months
...The repository emphasizes understanding the underlying principles of machine learning while also providing practical exercises and examples that allow learners to build and experiment with real models. Many sections include notebooks and code examples that demonstrate how algorithms are implemented and trained using modern machine learning frameworks. -
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DialoGPT
Large-scale pretraining for dialogue
...The model was trained on a massive dataset of approximately 147 million conversational exchanges extracted from Reddit discussion threads, allowing it to learn patterns of natural human conversation. DialoGPT provides multiple pretrained model sizes and includes code for training, fine-tuning, and evaluating dialogue generation models. The repository also contains scripts for preparing conversation datasets and reproducing experimental benchmarks related to conversational AI research. -
17
cortex
Production infrastructure for machine learning at scale
...Cortex handles many operational challenges associated with deploying AI systems, such as managing dependencies, orchestrating data pipelines, and scaling services under load. Developers can define machine learning pipelines as code using declarative configuration files, which simplifies the process of managing complex ML workflows. The platform supports integration with cloud environments and container orchestration systems so that applications can scale dynamically based on demand. It is designed to help teams focus on building machine learning logic rather than managing infrastructure details. -
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Codeball AI
AI Code Review that finds bugs and fast-tracks your code
Codeball is a code review AI that scores pull requests on a grade from 0 (needs careful review) to 1. Use Codeball to add labels to help you focus, auto-approve PRs, and more. The Codeball action is easy to use (sane defaults) and is highly customizable to fit your workflow when needed. Label PRs when you should review them with caution. Stay sharp, don't let the bugs pass through. -
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Bullet Physics SDK
Real-time collision detection and multi-physics simulation for VR
This is the official C++ source code repository of the Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc. We are developing a new differentiable simulator for robotics learning, called Tiny Differentiable Simulator, or TDS. The simulator allows for hybrid simulation with neural networks. -
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Python ML Jupyter Notebooks
Practice and tutorial-style notebooks
...The project provides numerous examples and tutorials covering classical machine learning techniques such as regression, classification, clustering, and dimensionality reduction. It includes code implementations that show how to build models using popular libraries like scikit-learn, NumPy, pandas, and Matplotlib. The repository is designed to help learners understand both the theory and practical implementation of machine learning algorithms through step-by-step code examples. Many notebooks include explanations of algorithm behavior, data preparation techniques, and evaluation methods for machine learning models. ... -
21
Byzer-lang
A low-code open-source programming language for data pipeline
Byzer (former MLSQL) is a low-code, open-sourced, and distributed programming language for data pipeline, analytics, and AI in a cloud-native way. Design protocol: Everything is a table. Byzer is a SQL-like language, to simplify data pipeline, analytics, and AI, combined with built-in algorithms and extensions. We believe that everything is a table, a simple and powerful SQL-like language can significantly reduce human efforts of data development without switching different tools. -
22
Termin-Bot
Telegram bot to get notifications about free appointments
...Sometimes it is tough to get a termin in public institutions and this bot is a way to automate termin checks and send Telegram notifications, if free termin was found. The code could be also considered as a template for subsequent development. The principle of bot operation is to refresh a webpage with needed appointments periodically [TERMIN_URL] and to recognize the change on it. E.g., the page always contains the phrase "No free appointments" [NO_TERMIN_FOUND_STRING]. Then some free appointments are added to the system, and the phrase "No free appointments" disappears. ... -
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Python Machine Learning 3rd Ed.
The "Python Machine Learning (3rd edition)" book code repository
Python Machine Learning 3rd Ed. repository contains the complete source code that accompanies the book Python Machine Learning by Sebastian Raschka and collaborators. The project provides implementations of machine learning algorithms and data science workflows described in the book, enabling readers to experiment with real code while studying theoretical concepts. The repository includes Python notebooks and scripts demonstrating techniques such as data preprocessing, classification, regression, clustering, neural networks, and model evaluation. ... -
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AirSim
A simulator for drones, cars and more, built on Unreal Engine
AirSim is an open-source, cross platform simulator for drones, cars and more vehicles, built on Unreal Engine with an experimental Unity release in the works. It supports software-in-the-loop simulation with popular flight controllers such as PX4 & ArduPilot and hardware-in-loop with PX4 for physically and visually realistic simulations. It is developed as an Unreal plugin that can simply be dropped into any Unreal environment. AirSim's development is oriented towards the goal of creating a... -
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BioNLP is an initiative by the University of Colorado Denver Health Sciences Center to create and distribute code, software, and data for applying natural language processing techniques to biomedical texts
