Search Results for "model-builder" - Page 76
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Showing 2225 open source projects for "model-builder"
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Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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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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VideoPose3D
Efficient 3D human pose estimation in video using 2D keypoint
...It builds on top of convolutional and temporal networks that map 2D joint coordinates over time to consistent 3D skeletons, enabling robust motion capture without specialized sensors. The model is trained on large motion capture datasets and can generalize well to unseen environments by leveraging temporal context for smoothing and error correction. By using only 2D detections (such as those from OpenPose or Detectron), it enables markerless 3D pose estimation with relatively lightweight computational requirements. The framework includes pretrained models, data preprocessing utilities, visualization tools, and evaluation scripts for standard benchmarks like Human3.6M. ... -
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NLP-Models-Tensorflow
Gathers machine learning and Tensorflow deep learning models for NLP
NLP-Models-Tensorflow is a collection of natural language processing model implementations built using the TensorFlow deep learning framework. The repository provides numerous examples of neural network architectures used in modern NLP research and applications, including text classification, language modeling, machine translation, and sentiment analysis. Each model implementation is designed to illustrate how common NLP architectures operate, such as recurrent neural networks, convolutional models for text processing, and transformer-style attention mechanisms. ... -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than... -
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Delta ML
Deep learning based natural language and speech processing platform
...Use configuration files to easily tune parameters and network structures. What you see in training is what you get in serving: all data processing and features extraction are integrated into a model graph. Text classification, named entity recognition, question and answering, text summarization, etc. Uniform I/O interfaces and no changes for new models. -
Stop vibe-debugging.AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
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TrashEmail
A hosted disposable email telegram bot; Extremely privacy friendly
TrashEmail is a hosted Telegram bot that can save your private email address by offering a disposable email address. It can create, and manage, disposable email addresses and link them with your telegram bot chat. -
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TFKit
Handling multiple nlp task in one pipeline
...It leverages the use of transformers on many tasks with different models in this all-in-one framework. All you need is a little change of config. You can use tfkit for model training and evaluation with tfkit-train and tfkit-eval. The key to combine different task together is to make different task with same data format. All data will be in csv format - tfkit will use csv for all task, normally it will have two columns, first columns is the input of models, the second column is the output of models. ... -
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NSFW Detection Machine Learning Model
Keras model of NSFW detector
Keras model of NSFW detector, NSFW Detection Machine Learning Model. -
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GPT2 for Multiple Languages
GPT2 for Multiple Languages, including pretrained models
...Batteries-included Colab demo. 1.5B GPT2 pretrained Chinese model (~30G corpus, 22w steps). -
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VoTT
Visual Object Tagging Tool, an electron app for building models
Visual Object Tagging Tool: An electron app for building end-to-end Object Detection Models from Images and Videos. An open source annotation and labeling tool for image and video assets. VoTT is a React + Redux Web application, written in TypeScript. This project was bootstrapped with Create React App. VoTT can be installed as a native application or run from source. VoTT is also available as a stand-alone Web application and can be used in any modern Web browser. VoTT is available for... -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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ModelDB
Open Source ML Model Versioning, Metadata, and Experiment Management
An open-source system for Machine Learning model versioning, metadata, and experiment management. ModelDB is an open-source system to version machine learning models including their ingredients code, data, config, and environment and to track ML metadata across the model lifecycle. -
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PyText
A natural language modeling framework based on PyTorch
...PyText addresses the often-conflicting requirements of enabling rapid experimentation and of serving models at scale. It achieves this by providing simple and extensible interfaces and abstractions for model components, and by using PyTorch’s capabilities of exporting models for inference via the optimized Caffe2 execution engine. We use PyText at Facebook to iterate quickly on new modeling ideas and then seamlessly ship them at scale. Distributed-training support built on the new C10d backend in PyTorch 1.0. Mixed precision training support through APEX (trains faster with less GPU memory on NVIDIA Tensor Cores). ... -
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SimpleAnnotator
A simple tool to annotate a text.
This tool allows the user to annotate by coloring portions of the text. This can be seen as a simple model of annotation. This tool has been built to complete particular experimentation on student behavior (annotation per example) facing particularly difficult content. We put it here as an open-source project. -
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Deep Learning cheatsheets
VIP cheatsheets for Stanford's CS 230 Deep Learning
...It was created to help students and practitioners quickly review important formulas, workflows, and implementation concepts without navigating large textbooks or lecture archives. The repository combines concise theoretical explanations with practical training advice, making it valuable for both interview preparation and hands-on model development. Its materials are widely used within the machine learning community because of their accessibility, clarity, and high information density. -
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DeepFaceLab
The leading software for creating deepfakes
...DeepFaceLab is an open-source deepfake system that enables users to swap the faces on images and on video. It offers an imperative and easy-to-use pipeline that even those without a comprehensive understanding of the deep learning framework or model implementation can use; and yet also provides a flexible and loose coupling structure for those who want to strengthen their own pipeline with other features without having to write complicated boilerplate code. DeepFaceLab can achieve results with high fidelity that are indiscernible by mainstream forgery detection approaches. ... -
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Aide
The open source AI-native IDE
Aide is an AI software engineering assistant that provides conversational code generation, analysis, and refactoring directly within your IDE or through a local web interface. Built to act as a full-stack collaborator, it understands multi-file projects, detects dependency relationships, and can generate consistent updates across files and frameworks. It supports multiple backends—including OpenAI, Anthropic, and open-source models—and can route requests based on task type or latency... -
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End-to-End Negotiator
Deal or No Deal? End-to-End Learning for Negotiation Dialogues
...The framework provides code for both supervised learning (training from human dialogue data) and reinforcement learning (via self-play and rollout-based planning). It introduces a hierarchical latent model, where high-level intents are first clustered and then translated into coherent language, improving dialogue diversity and goal consistency. The repository also includes the Negotiate dataset, comprising over 5,800 dialogues across 2,200 unique scenarios. -
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PyTorch GAN Zoo
A mix of GAN implementations including progressive growing
...It is built to support both researchers and developers who want to train, evaluate, and extend GANs efficiently across diverse datasets such as CelebA-HQ, FashionGen, DTD, and CIFAR-10. In addition to core GAN training, the repository includes tools for model evaluation, such as Inception Score and SWD metrics, as well as advanced features like GDPP for diverse generation and AC-GAN conditioning for class-specific synthesis. The framework also supports “inspirational generation,” enabling style or content transfer from reference images through pre-trained models. -
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StarGAN
Official PyTorch Implementation
StarGAN is an implementation of the Star Generative Adversarial Network, a model designed for multi-domain image-to-image translation using a single unified GAN architecture. Unlike earlier GAN approaches that required separate models for each domain pair, StarGAN enables flexible attribute transfer across multiple domains within one network, significantly improving efficiency and scalability. The repository includes full training and inference pipelines for tasks such as facial attribute manipulation and style transfer. ... -
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Tiny
Tiny Face Detector, CVPR 2017
...Pretrained model provided (ResNet101-based, plus alternatives). -
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TensorNets
High level network definitions with pre-trained weights in TensorFlow
High level network definitions with pre-trained weights in TensorFlow (tested with 2.1.0 >= TF >= 1.4.0). Applicability. Many people already have their own ML workflows and want to put a new model on their workflows. TensorNets can be easily plugged together because it is designed as simple functional interfaces without custom classes. Manageability. Models are written in tf.contrib.layers, which is lightweight like PyTorch and Keras, and allows for ease of accessibility to every weight and end-point. Also, it is easy to deploy and expand a collection of pre-processing and pre-trained weights. ... -
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NLP Best Practices
Natural Language Processing Best Practices & Examples
In recent years, natural language processing (NLP) has seen quick growth in quality and usability, and this has helped to drive business adoption of artificial intelligence (AI) solutions. In the last few years, researchers have been applying newer deep learning methods to NLP. Data scientists started moving from traditional methods to state-of-the-art (SOTA) deep neural network (DNN) algorithms which use language models pretrained on large text corpora. This repository contains examples and... -
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VGGFace2
VGGFace2 Dataset for Face Recognition
...The dataset was collected from Google Image Search, ensuring a wide diversity in ethnicity, profession, and real-world conditions. It is split into a training set with 8,631 identities and a test set with 500 identities, making it suitable for benchmarking and large-scale model training. Alongside the dataset, the repository provides pre-trained models based on ResNet-50 and SE-ResNet-50 architectures, trained with both MS-Celeb-1M pretraining and fine-tuning on VGGFace2. These models achieve strong verification performance on benchmarks such as IJB-B and include variants with lower-dimensional embeddings for compact feature representation. ... -
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textgenrnn
Easily train your own text-generating neural network
...Train the model using contextual labels, allowing it to learn faster and produce better results in some cases. -
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YouTokenToMe
Unsupervised text tokenizer focused on computational efficiency
YouTokenToMe is a fast and efficient unsupervised text tokenization library designed for training subword embeddings, particularly useful for NLP models. -
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CrypTen
A framework for Privacy Preserving Machine Learning
...Designed to make secure computation accessible to machine learning practitioners, CrypTen introduces a CrypTensor object that behaves like a regular PyTorch tensor, allowing users to seamlessly apply automatic differentiation and neural network operations. Its design mirrors PyTorch’s modular and library-based structure, enabling flexible experimentation, debugging, and model development. The framework supports both encryption and decryption of tensors and operations such as addition and multiplication over encrypted values. Although not yet production-ready, CrypTen focuses on advancing real-world secure ML applications, such as training and inference over private datasets, without exposing sensitive data.
