Search Results for "edex-ui-windows" - Page 75
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Showing 2637 open source projects for "edex-ui-windows"
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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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Horovod
Distributed training framework for TensorFlow, Keras, PyTorch, etc.
Horovod was originally developed by Uber to make distributed deep learning fast and easy to use, bringing model training time down from days and weeks to hours and minutes. With Horovod, an existing training script can be scaled up to run on hundreds of GPUs in just a few lines of Python code. Horovod can be installed on-premise or run out-of-the-box in cloud platforms, including AWS, Azure, and Databricks. Horovod can additionally run on top of Apache Spark, making it possible to unify data... -
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pyts
A Python package for time series classification
pyts is a Python package dedicated to time series classification. It aims to make time series classification easily accessible by providing preprocessing and utility tools, and implementations of several time series classification algorithms. The package comes up with many unit tests and continuous integration ensures new code integration and backward compatibility. The package is distributed under the 3-clause BSD license. -
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Poe is a platform for interacting with AI-based bots. That includes well-known chat bots like OpenAI's ChatGPT and Anthropic's Claude, but anyone can create their own bot by implementing the protocol described in this repository.
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ParlAI
A framework for training and evaluating AI models
ParlAI is a comprehensive research platform for building, training, and evaluating dialogue agents across a wide variety of tasks and datasets. It provides a unified interface—agents, teachers, and worlds—so the same model can be trained on multi-turn chit-chat, question answering, task-oriented dialogue, retrieval, or safety-focused datasets without changing core code. The library integrates tightly with PyTorch and supports both generative and retrieval-augmented models, along with... -
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CORL
High-quality single-file implementations of SOTA Offline
CORL (Collection of Reinforcement Learning Environments for Control Tasks) is a modular and extensible set of high-quality reinforcement learning environments focused on continuous control and robotics. It aims to offer standardized environments suitable for benchmarking state-of-the-art RL algorithms in control tasks, including physics-based simulations and custom-designed scenarios. -
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doccano client
A simple client for doccano API
doccano-client is a simple client wrapper for the doccano API. We're introducing a newly revamped Doccano API Client that features more Pythonic interaction as well as more testing and documentation. It also adds more regulated compatibility with specific Doccano release versions. -
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lora-svc
Singing voice change based on whisper, lora for singing voice clone
singing voice change based on whisper, and lora for singing voice clone. You will feel the beauty of the code from this project. Uni-SVC main branch is for singing voice clone based on whisper with speaker encoder and speaker adapter. Uni-SVC main target is to develop lora for SVC. With lora, maybe clone a singer just need 10 stence after 10 minutes train. Each singer is a plug-in of the base model. -
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Metaseq
Repo for external large-scale work
Metaseq is a flexible, high-performance framework for training and serving large-scale sequence models, such as language models, translation systems, and instruction-tuned LLMs. Built on top of PyTorch, it provides distributed training, model sharding, mixed-precision computation, and memory-efficient checkpointing to support models with hundreds of billions of parameters. The framework was used internally at Meta to train models like OPT (Open Pre-trained Transformer) and serves as a... -
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It is a powerful data scraping tool that helps you extract information from various online sources. Easily collect data from Google SERP, Maps, Shopify, Zillow, and more. With a user-friendly interface, you can scrape and save data in JSON or Excel formats. Unlock insights from the web effortlessly with scrape-it.cloud API.
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Stop Storing Third-Party Tokens in Your DatabaseRolling your own OAuth token storage can be a security liability. Token Vault securely stores access and refresh tokens from federated providers and handles exchange and renewal automatically. Connected accounts, refresh exchange, and privileged worker flows included.
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PRM800K
800,000 step-level correctness labels on LLM solutions to MATH problem
PRM800K is a process supervision dataset accompanying the paper Let’s Verify Step by Step, providing 800,000 step-level correctness labels on model-generated solutions to problems from the MATH dataset. The repository releases the raw labels and the labeler instructions used in two project phases, enabling researchers to study how human raters graded intermediate reasoning. Data are stored as newline-delimited JSONL files tracked with Git LFS, where each line is a full solution sample that... -
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TensorFlow Ranking
Learning to rank in TensorFlow
TensorFlow Ranking is a library for Learning-to-Rank (LTR) techniques on the TensorFlow platform. Commonly used loss functions including pointwise, pairwise, and listwise losses. Commonly used ranking metrics like Mean Reciprocal Rank (MRR) and Normalized Discounted Cumulative Gain (NDCG). Multi-item (also known as groupwise) scoring functions. LambdaLoss implementation for direct ranking metric optimization. Unbiased Learning-to-Rank from biased feedback data. We envision that this library... -
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Spektral
Graph Neural Networks with Keras and Tensorflow 2
...Spektral also includes lots of utilities for representing, manipulating, and transforming graphs in your graph deep learning projects. Spektral is compatible with Python 3.6 and above, and is tested on the latest versions of Ubuntu, MacOS, and Windows. Other Linux distros should work as well. The 1.0 release of Spektral is an important milestone for the library and brings many new features and improvements. -
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DiT (Diffusion Transformers)
Official PyTorch Implementation of "Scalable Diffusion Models"
DiT (Diffusion Transformer) is a powerful architecture that applies transformer-based modeling directly to diffusion generative processes for high-quality image synthesis. Unlike CNN-based diffusion models, DiT represents the diffusion process in the latent space and processes image tokens through transformer blocks with learned positional encodings, offering scalability and superior sample quality. The model architecture parallels large language models but for image tokens—each block... -
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Image to Text
Convert an image to text to spot intelligible words.
The program will convert to text an image, such as a photo , with the purpose of analyzing it to spot intelligible words. Use the program with photos of clouds, sea, soil, vegetation or any other photo of natural or man-made semi-homogeneous configuration, to reveal the hidden universal-philosophical messages of the image. You can also use it on photos of people or art pieces to have a psychological insight of the person portrayed or of the image author. The resulting text will be a long... -
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Lumi-HSP
This is an AI language model that can predict Heart failure or stroke
Using thsi AI model, you can predict the chances of heart stroke and heart failure. HIGLIGHTS : 1. Accuracy of this model is 95% 2. This model uses the powerful Machine Learning algorithm "GradientBoosting" for predicting the outcomes. 3. An easy to use model and accessible to everyone. -
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TF2DeepFloorplan
TF2 Deep FloorPlan Recognition using a Multi-task Network
TF2 Deep FloorPlan Recognition using a Multi-task Network with Room-boundary-Guided Attention. Enable tensorboard, quantization, flask, tflite, docker, github actions and google colab. This repo contains a basic procedure to train and deploy the DNN model suggested by the paper 'Deep Floor Plan Recognition using a Multi-task Network with Room-boundary-Guided Attention'. It rewrites the original codes from zlzeng/DeepFloorplan into newer versions of Tensorflow and Python. -
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DALL-E in Pytorch
Implementation / replication of DALL-E, OpenAI's Text to Image
Implementation / replication of DALL-E (paper), OpenAI's Text to Image Transformer, in Pytorch. It will also contain CLIP for ranking the generations. Kobiso, a research engineer from Naver, has trained on the CUB200 dataset here, using full and deepspeed sparse attention. You can also skip the training of the VAE altogether, using the pretrained model released by OpenAI! The wrapper class should take care of downloading and caching the model for you auto-magically. You can also use the... -
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TensorFlow Documentation
TensorFlow documentation
An end-to-end platform for machine learning. TensorFlow makes it easy to create ML models that can run in any environment. Learn how to use the intuitive APIs through interactive code samples. -
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VAMS
Virtual Assistant Maintenance System
Virtual Assistant Maintenance System also knowns as VAMS is an AI software application, that helps users with some computer maintenance issues. Application Requirements: Operating System: Windows 8.1/10 /11 Processor: Intel Core i5 or equivalent RAM: 4GB or higher Free Disk Space: 500MB -
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AB3DMOT
Official Python Implementation for "3D Multi-Object Tracking
AB3DMOT is a real-time 3D multi-object tracking framework designed for applications such as autonomous driving and robotics perception. The system processes detection results from 3D object detectors that analyze LiDAR point clouds and uses them to track multiple objects across consecutive frames. Its tracking pipeline relies on a combination of classical algorithms, including a Kalman filter for state estimation and the Hungarian algorithm for data association between detected objects and... -
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RasaGPT
Headless Rasa chatbot platform with LLM integration and APIs
RasaGPT is a headless chatbot platform that combines Rasa with modern LLM tooling such as Langchain and LlamaIndex. It serves as a reference implementation and boilerplate for building conversational AI systems with retrieval and context injection. RasaGPT includes a FastAPI backend for creating custom bot endpoints, along with document ingestion and a training pipeline. It simplifies integration challenges between Rasa and LLM libraries, including metadata handling and library conflicts.... -
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AI-Agent-Host
The AI Agent Host is a module-based development environment.
The AI Agent Host integrates several advanced technologies and offers a unique combination of features for the development of language model-driven applications. The AI Agent Host is a module-based environment designed to facilitate rapid experimentation and testing. It includes a docker-compose configuration with QuestDB, Grafana, Code-Server and Nginx. The AI Agent Host provides a seamless interface for managing and querying data, visualizing results, and coding in real-time. The AI... -
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Simple LLM Finetuner
Simple UI for LLM Model Finetuning
Simple LLM Finetuner is a beginner-friendly interface designed to make the process of fine-tuning large language models more accessible by providing a simplified UI and workflow built around parameter-efficient techniques such as LoRA. It allows users to customize pre-trained models using relatively small datasets and modest hardware, making it feasible to experiment with LLM training even on consumer-grade GPUs or cloud environments like Google Colab. The tool includes a web-based interface where users can input datasets, configure training parameters, and run fine-tuning jobs without deep knowledge of machine learning pipelines. ... -
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Pyrogram
Elegant, modern and asynchronous Telegram MTProto API framework
Pyrogram is a modern, elegant and asynchronous MTProto API framework. It enables you to easily interact with the main Telegram API through a user account (custom client) or a bot identity (bot API alternative) using Python. Ready: Install Pyrogram with pip and start building your applications right away. Easy: Makes the Telegram API simple and intuitive, while still allowing advanced usages. Elegant: Low-level details are abstracted and re-presented in a more convenient way. Fast: Boosted up... -
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unit-minions
AI R&D Efficiency Improvement Research: Do-It-Yourself Training LoRA
"AI R&D Efficiency Improvement Research: Do-It-Yourself Training LoRA", including Llama (Alpaca LoRA) model, ChatGLM (ChatGLM Tuning) related Lora training. Training content: user story generation, test code generation, code-assisted generation, text to SQL, text generation code.
