Search Results for "ofn-layer-aligner" - Page 4
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Showing 187 open source projects for "ofn-layer-aligner"
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Context for your AI agentsBuild data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.
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TensorLayer
Deep learning and reinforcement learning library for scientists
...This project can also be found at OpenI and Gitee. 3.0.0 has been pre-released, the current version supports TensorFlow, MindSpore and PaddlePaddle (partial) as the backends, allowing users to run the code on different hardware like Nvidia-GPU and Huawei-Ascend. In the future, it will support TensorFlow, MindSpore, PaddlePaddle, PyTorch and other backends. TensorLayer has a high-level layer/model abstraction which is effortless to learn. You can learn how deep learning can benefit your AI tasks in minutes through the massive examples. -
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ccplot
CloudSat and CALIPSO plotting tool
ccplot is an open source command-line program for plotting profile, layer and earth view data sets from CloudSat, CALIPSO and Aqua MODIS products. -
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Lambda Networks
Implementation of LambdaNetworks, a new approach to image recognition
Implementation of λ Networks, a new approach to image recognition that reaches SOTA on ImageNet. The new method utilizes λ layer, which captures interactions by transforming contexts into linear functions, termed lambdas, and applying these linear functions to each input separately. Shinel94 has added a Keras implementation! It won't be officially supported in this repository, so either copy / paste the code under ./lambda_networks/tfkeras.py or make sure to install tensorflow and keras before running the provided commands. -
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Chisel
A collection of LLDB commands to assist debugging iOS apps
Chisel is a collection of LLDB commands designed to assist you in the process of debugging iOS apps. All of the commands provided by Chisel come with verbose help. Be sure to read it when in doubt! You can add local, custom commands. There's also builtin support to make it super easy to specify the arguments and options that a command takes. See the border and pinvocation commands for example use. Developing commands, whether for local use or contributing to Chisel directly, both follow the... -
Teradata VantageCloud Enterprise is a data analytics platform for performing advanced analytics on AWS, Azure, and Google Cloud.VantageCloud is the complete cloud analytics and data platform, delivering harmonized data and Trusted AI for all. Built for performance, flexibility, and openness, VantageCloud enables organizations to unify diverse data sources, run complex analytics, and deploy AI models—all within a single, scalable platform.
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Clay Golem
Golem is creating a global market for computing power
The Golem Network fosters a global group of creators building ambitious software solutions that will shape the technological landscape of future generations by accessing computing resources across the platform. Golem Network is an accessible, reliable, open access and censorship-resistant protocol, democratizing access to digital resources and connecting users through a flexible, open-source platform. With Golem Network, users can connect with ease and pay each other for sharing their unused... -
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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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Python DB-API 2.0 module for ADO
Use Microsoft ADO to read/write most data bases.
Python module that makes it easy to use Microsoft ADO for connecting with databases and other data sources. For CPython users, this module is included as part of pywin32 (https://github.com/mhammond/pywin32), and continued support will take place there. This fork will be maintained for Iron Python users. * Documentation at http://adodbapi.sourceforge.net/quick_reference.pdf or quick_reference.odb in the .zip -
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BoTube2
IRC Bot
BoTube2 is another IRC BOT with an advanced plugin system that makes easy to develop new capabilities, by now there are only 12 plugins developed, you can develop more if you want. Added first revision of documentation for the plugin developer (spanish only by now). Would you like to enpower Botube2 with your own plugin? Lots of bugfixes here! -
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yapydata
Lower-Layer unified data - JSON, XML, YAML + INI, CFG, properties
...Therefore it encapsulates the libraries by offering a common API with the canonical internal data as JSON compatible Python in-memory structure. The application is foreseen in particular for the lower layer of the software stack including setup-tools. Thus it uses standard libraries only whenever possible. The initial supported DDLs are: * JSON, XML, YAML and the formats * INI, CFG, .properties The yapydata in particular supports the advanced access to data entries by mapping the dotted-OID notation onto mixed in-memory data types, optional including non-conformant tyeps such as tuple and set. -
Deliver trusted data with dbtData teams use dbt to codify business logic and make it accessible to the entire organization—for use in reporting, ML modeling, and operational workflows.
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setupdocx
Multidocument automation by templates - for sphinx, mkdocs, epydoc ...
The ‘setupdocx‘ provides a control layer for continuous documentation by the simplified creation, packaging, and installation of documentation. The provided commands are distributed as entry points and optional base classes for further customization into 'setup.py' - setuptools / distutils. Manages arbitrary document templates for the supported builder, supports multiple builds with arbitrary document layouts, designs, and patched contents. -
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yapyutils
Utilities for platform indepentent low-level system APIs.
...These are e.g. used for extensions of the *setuptools* and *distutils*, thus reduce the package dependency and avoid circular dependencies whenever possible by using standard packages and classes only. The more complex and complete data packages are provided for higher application layer functionality. The current release contains: * *yapyutils.modules* A utility to locate and load modules by a given name and/or file system path name, based on the *sys.path* variable. * *yapyutils.files* Search and location of files, e.g. modules and configuration files. * *yapyutils.help* Simple help for command line interfaces... -
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SimpleITK: a simplified layer build on top of the Insight Toolkit (ITK), intended to facilitate its use in rapid prototyping, education and interpreted languages.
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FID score for PyTorch
Compute FID scores with PyTorch
...However, due to differences in the image interpolation implementation and library backends, FID results still differ slightly from the original implementation. In difference to the official implementation, you can choose to use a different feature layer of the Inception network instead of the default pool3 layer. -
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CakeChat
CakeChat: Emotional Generative Dialog System
...Embedding layer may be either fixed or fine-tuned along with other weights of the network. -
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WhatsappToDesktop
Esse é um pacote de compilado do Whatsapp Web versão 1.0.
Esse é um pacote de compilado do Whatsapp Web versão 1.0. Esse é um aplicativo multiplataforma de mensagens instantâneas e chamadas de voz para smartphones. Além de mensagens de texto, os usuários podem enviar vídeos, vídeos e documentos em formato PDF, além de fazer a livre conexão com o meio de uma conexão com internet ... -
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Skater
Python library for model interpretation/explanations
Skater is a unified framework to enable Model Interpretation for all forms of the model to help one build an Interpretable machine learning system often needed for real-world use-cases(** we are actively working towards to enabling faithful interpretability for all forms models). It is an open-source python library designed to demystify the learned structures of a black box model both globally(inference on the basis of a complete data set) and locally(inference about an individual... -
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Madara
Middleware for distributed applications
...MADARA is composed of several tools and middleware, and the main entry point into the system is the Knowledge and Reasoning Language (KaRL) Engine, which provides a real-time scripting language for nanosecond execution times hooked into a flexible transport layer for distributed reasoning. The KaRL engine also supports object-oriented C++, Java, and Python programming through Containers, classes that provide abstractions and references for variable location within the KaRL Knowledge Base. This project is currently in process of being ported from http://madara.googlecode.com. -
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pyhanlp
Chinese participle
...The project focuses on making HanLP’s capabilities accessible through a Python-friendly API surface, so you can integrate NLP steps into data pipelines, notebooks, and downstream ML or information-extraction code. In practice, it serves as a bridge layer: Python calls are translated into the corresponding HanLP operations, so you can keep your application logic in Python while relying on HanLP’s implementations. It is especially useful when you need a pragmatic “get results quickly” NLP layer for segmentation, tagging, entity extraction, parsing, or keyword-style tasks rather than experimenting with model training from scratch. -
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FAKE2DB
Create custom test databases that are populated with fake data
Generate fake but valid data filled databases for test purposes using most popular patterns(AFAIK). Current support is sqlite, mysql, postgresql, mongodb, redis, CouchDB. The installation through pypi retrieves 'fake-factory' as a main dependency. db argument takes 6 possible options, sqlite, mysql, postgresql, mongodb, redis, CouchDB. name argument is OPTIONAL. When it is absent fake2db will name db's randomly. host argument is OPTIONAL. Hostname to use for database connection. Not used for... -
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Database mapping layer for MongoDB on Python. Includes schema enforcement and some facilities for schema migration.
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Image classification models for Keras
Keras code and weights files for popular deep learning models
All architectures are compatible with both TensorFlow and Theano, and upon instantiation the models will be built according to the image dimension ordering set in your Keras configuration file at ~/.keras/keras.json. For instance, if you have set image_dim_ordering=tf, then any model loaded from this repository will get built according to the TensorFlow dimension ordering convention, "Width-Height-Depth". Pre-trained weights can be automatically loaded upon instantiation (weights='imagenet'... -
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txObject ATK is an OS independent C++ & Python object library. Built in the 90s, it provides a 5-layer framework: Object Library, IO / Timers, Threads, Inter-Process / Distributed Object Communication
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Seq2seq Chatbot for Keras
This repository contains a new generative model of chatbot
...The canonical seq2seq model became popular in neural machine translation, a task that has different prior probability distributions for the words belonging to the input and output sequences since the input and output utterances are written in different languages. The architecture presented here assumes the same prior distributions for input and output words. Therefore, it shares an embedding layer (Glove pre-trained word embedding) between the encoding and decoding processes through the adoption of a new model. -
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PrettyTensor
Pretty Tensor: Fluent Networks in TensorFlow
Pretty Tensor is a high-level API built on top of TensorFlow that simplifies the process of creating and managing deep learning models. It wraps TensorFlow tensors in a chainable object syntax, allowing developers to build multi-layer neural networks with concise and readable code. Pretty Tensor preserves full compatibility with TensorFlow’s core functionality while providing syntactic sugar for defining complex architectures such as convolutional and recurrent networks. The library’s design emphasizes flexibility and modularity, supporting advanced features like default scopes, parameter templates, and variable reuse. ... -
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PyDal is a pure Python database abstraction layer. It provides a DBAPI 2.0 wrapper for DBAPI 2.0 drivers. Sounds strange, but even drivers that fully conform to the API can differ enough to make building database independent applications difficult.
