Search Results for "task"
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Showing 19 open source projects for "task"
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colleague-skill
Transform a cold separation into a warm Skill
colleague-skill is a specialized agent skill designed to simulate a collaborative teammate within AI-driven workflows, enabling agents to behave more like human colleagues in problem-solving scenarios. The project focuses on enhancing interaction quality by introducing role-based behavior, contextual awareness, and cooperative task execution. It allows agents to provide suggestions, feedback, and alternative approaches, mimicking real-world collaboration dynamics. The system likely integrates with broader agent frameworks, enabling seamless inclusion in multi-agent environments. It emphasizes communication and coordination, ensuring that agents can contribute meaningfully to shared objectives. ... -
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Stock prediction deep neural learning
Predicting stock prices using a TensorFlow LSTM
Predicting stock prices can be a challenging task as it often does not follow any specific pattern. However, deep neural learning can be used to identify patterns through machine learning. One of the most effective techniques for series forecasting is using LSTM (long short-term memory) networks, which are a type of recurrent neural network (RNN) capable of remembering information over a long period of time. -
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Amazon Braket Python Schemas
A library that contains schemas for Amazon Braket
Amazon Braket Python Schemas is an open source library that contains the schemas for Braket, including intermediate representations (IR) for Amazon Braket quantum tasks and offers serialization and deserialization of those IR payloads. Think of the IR as the contract between the Amazon Braket SDK and Amazon Braket API for quantum programs. Schemas for the S3 results of each quantum task. Schemas for the device capabilities of each device. The preferred way to get Amazon Braket Python Schemas is by installing the Amazon Braket Python SDK, which will pull in the schemas. You can install from source by cloning this repository and running a pip install command in the root directory of the repository. There are currently two types of IR, including jaqcd (JsonAwsQuantumCircuitDescription) and annealing. -
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FairChem
FAIR Chemistry's library of machine learning methods for chemistry
...The centerpiece models (e.g., UMA variants) plug directly into the ASE ecosystem via a FAIRChem calculator, so users can run relaxations, molecular dynamics, spin-state energetics, and surface catalysis workflows with the same pretrained network by switching a task flag. Tasks span heterogeneous domains—catalysis (OC20-style), inorganic materials (OMat), molecules (OMol), MOFs (ODAC), and molecular crystals (OMC)—allowing one model family to serve many simulations. The README provides quick paths for pulling models (e.g., via Hugging Face access), then running energy/force predictions on GPU or CPU. -
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Multimodal
TorchMultimodal is a PyTorch library
This project, also known as TorchMultimodal, is a PyTorch library for building, training, and experimenting with multimodal, multi-task models at scale. The library provides modular building blocks such as encoders, fusion modules, loss functions, and transformations that support combining modalities (vision, text, audio, etc.) in unified architectures. It includes a collection of ready model classes—like ALBEF, CLIP, BLIP-2, COCA, FLAVA, MDETR, and Omnivore—that serve as reference implementations you can adopt or adapt. ... -
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redis-py
Redis Python client
...It supports all Redis commands and data types, making it easy to build caching, messaging, or real-time analytics features in Python applications. With both synchronous and asyncio support, redis-py is suited for modern Python projects and integrates smoothly into web frameworks, task queues, and backend services. -
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Helium
Lighter web automation with Python
...It replaces verbose boilerplate code with natural language-like API calls such as click("Login") or write("hello", into="Name"). Helium manages browser setup, waits, and teardown, enabling quick development of scripts for testing, scraping, or task automation without requiring deep Selenium knowledge. -
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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
Tunix
A JAX-native LLM Post-Training Library
...Tunix also leans into research ergonomics: logging, checkpointing, and metrics are built in, and the code is written to be hackable rather than monolithic. Overall it aims to shorten the path from an off-the-shelf base model to a well-aligned, task-ready model using scalable JAX primitives. -
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Transformers4Rec
Transformers4Rec is a flexible and efficient library
...In some cases, it might be a repeated purchase or song play. User interests can also suffer from interest drift because preferences can change over time. Those challenges are addressed by the sequential recommendation task. -
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Amazon Braket Strawberry Fields Plugin
An open source framework for using Amazon Braket devices
...The Amazon Braket Python SDK is an open source library that provides a framework to interact with quantum computing hardware devices and simulators through Amazon Braket. This plugin provides the classes BraketEngine for submitting photonic circuits to Amazon Braket and BraketJob for tracking the status of the Braket task. Strawberry Fields is an open source library for writing and running programs for photonic quantum computers. BraketEngine and BraketJob have the same interfaces as RemoteEngine in Strawberry Fields and Job in the Xanadu Cloud Client, respectively, and can be used as drop-in replacements. -
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PyTorch Transfer-Learning-Library
Transfer Learning Library for Domain Adaptation, Task Adaptation, etc.
TLlib is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms or readily apply existing algorithms. We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please... -
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Awesome Graph Classification
Graph embedding, classification and representation learning papers
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers with reference implementations. Relevant graph classification benchmark datasets are available. Similar collections about community detection, classification/regression tree, fraud detection, Monte Carlo tree search, and gradient boosting papers with implementations. -
14
gradslam
gradslam is an open source differentiable dense SLAM library
...The question of “representation” is central in the context of dense simultaneous localization and mapping (SLAM). Newer learning-based approaches have the potential to leverage data or task performance to directly inform the choice of representation. However, learning representations for SLAM has been an open question, because traditional SLAM systems are not end-to-end differentiable. In this work, we present gradSLAM, a differentiable computational graph take on SLAM. Leveraging the automatic differentiation capabilities of computational graphs, gradSLAM enables the design of SLAM systems that allow for gradient-based learning across each of their components, or the system as a whole. -
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NLP Architect
A model library for exploring state-of-the-art deep learning
...NLP Architect is designed to be flexible for adding new models, neural network components, data handling methods, and for easy training and running models. NLP Architect is a model-oriented library designed to showcase novel and different neural network optimizations. The library contains NLP/NLU-related models per task, different neural network topologies (which are used in models), procedures for simplifying workflows in the library, pre-defined data processors and dataset loaders and misc utilities. The library is designed to be a tool for model development: data pre-processing, build model, train, validate, infer, save or load a model. -
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AdaNet
Fast and flexible AutoML with learning guarantees
...At each iteration, it measures the ensemble loss for each candidate, and selects the best one to move onto the next iteration. Adaptive neural architecture search and ensemble learning in a single train call. Regression, binary and multi-class classification, and multi-head task support. A tf.estimator.Estimator API for training, evaluation, prediction, and serving models. -
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RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
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aeneas
Automagically synchronize audio and text (aka forced alignment)
aeneas is a Python/C library and a set of tools to automagically synchronize audio and text (aka forced alignment). aeneas automatically generates a synchronization map between a list of text fragments and an audio file containing the narration of the text. In computer science this task is known as (automatically computing a) forced alignment. -
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C Library to manage a pool of event/task in a persistent way to assure that your events/tasks won't be deleted because of a failure. Events/tasks are saved on a FS. if FS is NFS, NFS availability checks are made. (comes with a python binding)
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