flyte
label-studio
flyte | label-studio | |
---|---|---|
31 | 50 | |
4,761 | 16,546 | |
1.9% | 2.5% | |
9.8 | 9.8 | |
7 days ago | 1 day ago | |
Go | JavaScript | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
flyte
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First 15 Open Source Advent projects
9. Flyte by Union AI | Github | tutorial
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Flyte 1.10: Self-hosted solution to build production-grade data and ML pipelines; now ships with monorepo, new agents and sensors, eager workflows and more π (4.1k stars on GitHub)
GitHub: https://github.com/flyteorg/flyte
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Flyte: Open-source orchestrator for building production-grade ML pipelines
This is actually but a link to Flyte, this is a link to the documentation for the Flyte integration in LangChain, a separate product.
Flyte's homepage is https://flyte.org/
- Flyte: Advanced workflow orchestration alternative to Apache Airflow
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Orchestration: Thoughts on Dagster, Airflow and Prefect?
Anyone tried Flyte?
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Flyte 1.6.0: Self-hosted solution to build production-grade data and ML pipelines; now ships with PyTorch elastic training, image specification without dockerfile, enhanced task execution insights and more π (3.4k stars on GitHub)
Website: https://flyte.org/
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Flyte(v1.5.0) - Self-hosted solution to build production-grade data and ML pipelines; now ships with streaming support, pod templates, partial tasks and more π (3.2k stars on GitHub)
Flyte is an open source orchestration tool for managing the workflow of machine learning and AI projects. It runs on top of Kubernetes.
- Flyte: Open-Source Kubernetes-Native ML Orchestrator Implemented in Go
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What is MLOps and how to get started? | MLOps series | Deploying ML in production
I have a question though, what is your opinion on https://flyte.org. My pipeline uses this and itβll be interesting to get your perspectives on itβs capabilities.
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Github alternative for ML?
Have you looked at flyte.org. It aims to bring "versioning", "compute" and "reproducibility" together in one package.
label-studio
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Annotation is dead
If instead you have a cohort on hand β -i.e., you do not want to send your data to a third party for any reason, or perhaps you have energetic undergrads β -then you could alternatively consider local, open-source annotation such as CVAT and Label Studio. Finally, nowadays, you might instead work with Large Multimodal Models to have them annotate your data; more on this awkward angle later.
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First 15 Open Source Advent projects
14. LabelStudio by Human Signal | Github | tutorial
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
For instance, the COCO Annotator is a web-based image annotation tool tailored for the COCO dataset format, allowing collaborative labeling with features like attribute tagging and automatic segmentation. Similarly, Label Studio offers an easy-to-use interface for bounding box object labeling in images.
- FLaNK Stack Weekly for 14 Aug 2023
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You Can't Have a Free Software AI Stack
Huh?
I wrote my own system for classifying a stream of texts in Python, I might Open Source it one of these days but I have to get it to the point where it is modular enough that I can customize it to do the particular things I want without subjecting people to my whims... I use it every day and I'm not afraid to demo it because it is rock solid.
My understanding is that my system would not be hard to adapt to work on images for certain kinds of tasks.
Pytorch is open source, Huggingface is open source. CUDA isn't. This is
https://labelstud.io/
and for annotating text spans there are so many open source tools
https://github.com/doccano/doccano
I worked for a company a few years back that built annotation tools for projects we sold to customers but never quite got to a polished general purpose annotator. Today there are an overwhelming number of companies in this space and products I never heard of, many of which are cloud based or paid. Looks like a gold rush to me.
- Label Studio: Open-Source Data Labeling Platform
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Best (quickest) way to annotate images for whole-image classification?
LabelStudio is free for single use. https://labelstud.io/
- Label Studio β Free multi-type data ML labeling and annotation tool
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Way to label yolov7 images fast
LabelStudio is pretty nice, and free & open source, but I have yet to try out their ML integration with a YOLO object detection model.
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image labeling online Tools
Label Studio is an open source data labeling tool that includes annotation functionality. It provides a simple user interface (UI) that lets you label various data types, including text, audio, time series data, videos, and images, and export the information to various model formats.
What are some alternatives?
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
cvat - Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/cvat-ai/cvat]
argo - Workflow Engine for Kubernetes
doccano - Open source annotation tool for machine learning practitioners.
temporal - Temporal service
awesome-data-labeling - A curated list of awesome data labeling tools
kubeflow - Machine Learning Toolkit for Kubernetes
diffgram - The AI Datastore for Schemas, BLOBs, and Predictions. Use with your apps or integrate built-in Human Supervision, Data Workflow, and UI Catalog to get the most value out of your AI Data.
Celery-Kubernetes-Operator - An operator to manage celery clusters on Kubernetes (Work in Progress)
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
Kedro - Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
labelbox-custom-labeling-apps - Explore example custom labeling apps built with Labelbox SDK