Agnostiq (AgnostiqHQ)

Agnostiq

AgnostiqHQ

Geek Repo

Developing Software for Advanced Computing

Location:Toronto

Home Page:https://agnostiq.ai

Twitter:@AgnostiqHQ

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Agnostiq's repositories

covalent

Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.

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multi-agent-llm

Lean implementation of various multi-agent LLM methods, including Iteration of Thought (IoT)

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covalent-slurm-plugin

Executor plugin interfacing Covalent with Slurm

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covalent-aws-plugins

Executor plugins interfacing Covalent with various AWS compute platforms

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Quantum-Variational-Rewinding

Covalent demonstration of the QVR algorithm using a cryptocurrency time series use case

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covalent-awsbatch-plugin

Executor plugin interfacing Covalent with AWS Batch

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covalent-executor-template

Template repository used to create new Covalent executors

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covalent-kubernetes-plugin

Executor plugin interfacing Covalent with Kubernetes

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covalent-ssh-plugin

Executor plugin interfacing Covalent with remote backends using SSH

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tutorials_covalent_pydata_2023

Covalent tutorial notebooks and slides for PyData 2023, NYC

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covalent-awslambda-plugin

Executor plugin interfacing Covalent with AWS Lambda

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covalent-cloud-github-workflow

Template for integrating Covalent Cloud's high-performance computing capabilities into GitHub Workflows

covalent-ec2-plugin

Executor plugin interfacing Covalent with Amazon EC2

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covalent-braket-plugin

Executor plugin interfacing Covalent with Amazon Braket Hybrid Jobs

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covalent-ecs-plugin

Executor plugin interfacing Covalent with Amazon ECS Fargate

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tutorials_covalent_ieee_2022

Tutorials for 2022 IEEE Quantum Week Workshop on Covalent

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covalent-azurebatch-plugin

Executor plugin interfacing Covalent with Azure Batch

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covalent-docker-dev

Dockerfiles used for building and developing Covalent in various environments

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covalent-gcpbatch-plugin

Executor plugin interfacing Covalent with GCP Batch

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tutorials_covalent_qsite_2022

Covalent tutorial for Q-Site conference 2022

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covalent_tutorials_ieee_2023

Tutorial notebooks for QCE at IEEE 2023 in Bellevue, Washington

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lag-llama

Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

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langchain

⚡ Building applications with LLMs through composability ⚡

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qml

Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.

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thefullstack

Source for https://fullstackdeeplearning.com

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