Search Results for "shader model 2.0)"
Sort By:
Showing 151 open source projects for "shader model 2.0)"
View related business solutions-
Over two-thirds of people reuse passwords across sites, resulting in an increasingly insecure e-commerce ecosystem. Learn how passwordless can not only mitigate these issues but make the authentication experience delightful. Implement Auth0 in any application in just five minutes
-
Out-of-the-box scripts. Around-the-clock monitoring. Unmatched automation capabilities. Start doing more with less and exceed service delivery expectations.
-
1
AWS Serverless Application Model
An open-source framework for building serverless applications
The AWS Serverless Application Model (SAM) is an open-source framework for building serverless applications. It provides shorthand syntax to express functions, APIs, databases, and event source mappings. With just a few lines per resource, you can define the application you want and model it using YAML. During deployment, SAM transforms and expands the SAM syntax into AWS CloudFormation syntax, enabling you to build serverless applications faster. To get started with building SAM-based... -
2
Alphafold
Open source code for AlphaFold
This package provides an implementation of the inference pipeline of AlphaFold v2.0. This is a completely new model that was entered in CASP14 and published in Nature. For simplicity, we refer to this model as AlphaFold throughout the rest of this document. Any publication that discloses findings arising from using this source code or the model parameters should cite the AlphaFold paper. Please also refer to the Supplementary Information for a detailed description of the method. You can use... -
3
OpenAssistant
Chat-based assistant that understands tasks
... the world interested in bringing this technology to everyone. The code and models are licensed under the Apache 2.0 license. Open Assistant will be free to use and modify. There will be versions which will be runnable on consumer hardware. You do not need to run the project locally unless you are contributing to the development process. The website link above will take you to the public website where you can use the data collection app. -
4
SageMaker TensorFlow Training Toolkit
Toolkit for running TensorFlow training scripts on SageMaker
Toolkit for running TensorFlow training scripts on SageMaker. SageMaker TensorFlow Training Toolkit is an open-source library for using TensorFlow to train models on Amazon SageMaker. To use your TensorFlow Serving model on SageMaker, you first need to create a SageMaker Model. After creating a SageMaker Model, you can use it to create SageMaker Batch Transform Jobs for offline inference, or create SageMaker Endpoints for real-time inference. A SageMaker Model contains references... -
Google Cloud is a cloud-based service that allows you to create anything from simple websites to complex applications for businesses of all sizes.
-
5
SageMaker Inference Toolkit
Serve machine learning models within a Docker container
Serve machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. Once you have a trained model, you can include it in a Docker container that runs your inference code. A container provides an effectively isolated environment, ensuring a consistent runtime regardless of where... -
6
Django Lifecycle Hooks
Declarative model lifecycle hooks, an alternative to Signals
This project provides a @hook decorator as well as a base model and mixin to add lifecycle hooks to your Django models. Django's built-in approach to offering lifecycle hooks is Signals. However, my team often finds that Signals introduce unnecessary indirection and are at odds with Django's "fat models" approach. Django Lifecycle Hooks supports Python 3.7, 3.8 and 3.9, Django 2.0.x, 2.1.x, 2.2.x, 3.0.x, 3.1.x, and 3.2.x. For simple cases, you might always want something to happen at a certain... -
7
OpenVINO Training Extensions
Trainable models and NN optimization tools
OpenVINO™ Training Extensions provide a convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference. When ote_cli is installed in the virtual environment, you can use the ote command line interface to perform various actions for templates related to the chosen task type, such as running, training, evaluating, exporting, etc. ote train trains a model (a particular model template) on a dataset and saves results in two files. ote... -
8
SageMaker Hugging Face Inference Toolkit
Library for serving Transformers models on Amazon SageMaker
SageMaker Hugging Face Inference Toolkit is an open-source library for serving Transformers models on Amazon SageMaker. This library provides default pre-processing, predict and postprocessing for certain Transformers models and tasks. It utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. For the Dockerfiles used for building SageMaker Hugging Face Containers, see AWS Deep Learning Containers. The SageMaker Hugging... -
9
KerasTuner
A Hyperparameter Tuning Library for Keras
KerasTuner is an easy-to-use, scalable hyperparameter optimization framework that solves the pain points of hyperparameter search. Easily configure your search space with a define-by-run syntax, then leverage one of the available search algorithms to find the best hyperparameter values for your models. KerasTuner comes with Bayesian Optimization, Hyperband, and Random Search algorithms built-in, and is also designed to be easy for researchers to extend in order to experiment with new search... -
Don’t settle when it comes to managing your clients’ IT infrastructure. Exceed their expectations with ConnectWise RMM, our MSP RMM software that provides proactive tools and NOC services—regardless of device environment. With the number of new vulnerabilities rising each year, smart patching procedures have never been more important. We automatically test and deploy patches when they are viable and restrict patches that are harmful. Get better protection for clients while you spend less time managing endpoints and more time growing your business. It’s tough to locate, afford, and retain quality talent. In fact, 81% of IT leaders say it’s hard to find the recruits they need. Add ConnectWise RMM, NOC services and get the expertise and problem resolution you need to become the advisor your clients demand—without adding headcount.
-
10
Opacus
Training PyTorch models with differential privacy
..., modular API for differential privacy research. Everyone is welcome to contribute. ML practitioners will find this to be a gentle introduction to training a model with differential privacy as it requires minimal code changes. Differential Privacy researchers will find this easy to experiment and tinker with, allowing them to focus on what matters. -
11
SageMaker Experiments Python SDK
Experiment tracking and metric logging for Amazon SageMaker notebooks
... to compare together. Trial: A description of a multi-step machine learning workflow. Each step in the workflow is described by a Trial Component. There is no relationship between Trial Components such as ordering. Trial Component: A description of a single step in a machine learning workflow. For example data cleaning, feature extraction, model training, model evaluation, etc. -
12
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. -
13
TextBox
A text generation library with pre-trained language models github.com
TextBox 2.0 is an up-to-date text generation library based on Python and PyTorch focusing on building a unified and standardized pipeline for applying pre-trained language models to text generation. From a task perspective, we consider 13 common text generation tasks such as translation, story generation, and style transfer, and their corresponding 83 widely-used datasets. From a model perspective, we incorporate 47 pre-trained language models/modules covering the categories of general... -
14
drf-yasg
Automated generation of real Swagger/OpenAPI 2.0 schemas
... a look at drf-spectacular, which is an actively maintained new library that shares most of the goals of this project, while working with OpenAPI 3.0 schemas. OpenAPI 3.0 provides a lot more flexibility than 2.0 in the types of API that can be described. drf-yasg is unlikely to soon, if ever, get support for OpenAPI 3.0. -
15
YData Synthetic
Synthetic data generators for tabular and time-series data
.... It consists a set of different GANs architectures developed using Tensorflow 2.0. Several example Jupyter Notebooks and Python scripts are included, to show how to use the different architectures. YData synthetic has now a UI interface to guide you through the steps and inputs to generate structure tabular data. The streamlit app is available form v1.0.0 onwards. -
16
ruDALL-E
Generate images from texts. In Russian
We present a family of generative models from SberDevices and Sber AI! Models allow you to create images that did not exist before. All you need is a text description in Russian or another language. Try to create unique images together with generative artists using your own formulations. Ask generative artists to depict something special for you as well. The Kandinsky 2.0 model uses the reverse diffusion method and creates colorful images on various topics in a matter of seconds by text query... -
17
SageMaker MXNet Inference Toolkit
Toolkit for allowing inference and serving with MXNet in SageMaker
SageMaker MXNet Inference Toolkit is an open-source library for serving MXNet models on Amazon SageMaker. This library provides default pre-processing, predict and postprocessing for certain MXNet model types and utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning... -
18
FreeCAD
a parametric 3D CAD modeler
... and customization. FreeCAD is based on OpenCasCade, a powerful geometry kernel, features an Open Inventor-compliant 3D scene representation model provided by the Coin 3D library, and a broad Python API. The interface is built with Qt. FreeCAD runs exactly the same way on Windows, Mac OSX and Linux platforms. -
19
A powerful editor for video games based on or similar to id Software's series of Quake games. Currently QuArK supports 41 distinct games, 5 generic game engines, and a countless number of expansions packs, addons, and mods. It integrates a map editor, model editor, archive editors, texture management, and much more.
-
20
GenX
X-Ray and Neutron Reflectivity Modeling
GenX is a scientific program to refine x-ray refelcetivity, neutron reflectivity and surface x-ray diffraction data using the differential evolution algorithm. GenX is very modular and highly extensible and can be used as a general fitting program. -
21
A multimedia authoring and processing framework and a video playout server for television broadcasting.
-
22
CAMPARI
Software for molecular simulations and trajectory analysis
We are proud to introduce version 5 of CAMPARI. We have added a number of new features, most notably a Python interface for interpreting user-supplied code (with the help of ForPy), a novel trajectory storage standard (with the help of libpqxx/PostgreSQL), and a module for performing transition path theory. Naturally, CAMPARI continues to provide the reference implementation of the ABSINTH force field paradigm and implicit solvation model. CAMPARI is a joint package for performing... -
23
ANUGA is a software implementation of a hydrodynamic model which is specifically designed to model wetting and drying processes. ANUGA is a joint development project between Geoscience Australia (GA) and the Australian National University (ANU). ANUGA is now being developed on github at https://github.com/anuga-community/anuga_core For information on ANUGA please go to http://anuga.anu.edu.au The ANUGA project is described on http://en.wikipedia.org/wiki/ANUGA_Hydro
-
24
Linux-based DIY DCC (Model Railroad Digital Command Control) The project has morphed somewhat from its starting point. There's now a LOT of hardware bits, designed in CadSoft Eagle (V7, not the AutoDesk versions) and low-level code for PIC and ARM embedded micros. The Linux kernel driver for the original hardware is still there but increasingly redundant.
-
25
TOMUSS
TOMUSS: The Online Multi User Simple Spreadsheet
TOMUSS is an interactive web application (groupware) allowing multiple concurrent users to edit data tables. Its primary goal is the management of students grades.