Markup Alternatives
Similar projects and alternatives to markup based on common topics and language
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xtreme1
Xtreme1 is an all-in-one data labeling and annotation platform for multimodal data training and supports 3D LiDAR point cloud, image, and LLM.
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SurveyJS
Open-Source JSON Form Builder to Create Dynamic Forms Right in Your App. With SurveyJS form UI libraries, you can build and style forms in a fully-integrated drag & drop form builder, render them in your JS app, and store form submission data in any backend, inc. PHP, ASP.NET Core, and Node.js.
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force-multiplier
Use AI to edit your documents in real-time. Provide feedback and let the AI do all the work.
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datalabel
datalabel is a UI-based data editing tool that makes it easy to create labeled text data in a dataframe. With datalabel, you can quickly and effortlessly edit your data without having to write any code. Its intuitive interface makes it ideal for both experienced data professionals and those new to data editing.
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refinery
The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.
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argilla
Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
markup reviews and mentions
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Show HN: An annotation tool for ML and NLP
Hey HN! I'm super excited to share Markup with you, which is a totally free & open-source annotation tool that helps you transform unstructured text (e.g. news articles) into structured data that you can use for building, training, or fine-tuning ML models!
Check it out: https://github.com/samueldobbie/markup
Just to preface this summary, it's all a bit hacked together at the moment, and I'm in the process of rewriting the tool from scratch so this description is privy to change.
To generate the suggestions there's an active learner with an underlying random forest classifier, that has been fed ~60 seed sentences [1], to classify positive sentences (e.g. contains a prescription) and negative sentences (e.g. doesn't contain a prescription).
All positive sentences are fed into a sequence-to-sequence RNN model, that has been trained on ~50k synthetic rows of data [2] which maps unstructured sentences (e.g. patient is on pheneturide 250mg twice a day) to a structured output with the desired features (e.g. name: pheneturide; dose: 285; unit: g; frequency: 2). These synthetic sentences were generated with the in-built data generator [3].
The outputs of the RNN are validated to ensure they meet the expected structure and are valid for the sentence (e.g. the predicted drug name must exist somewhere within the sentence).
All non-junk predictions are shown to the user who can accept, edit, or reject each. Based on the users' response, the active learner is refined (currently nothing is fed back into the RNN).
[1] https://github.com/samueldobbie/markup/blob/master/data/text...
[2] https://raw.githubusercontent.com/samueldobbie/markup/master...
[3] https://www.getmarkup.com/tools/data-generator/
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samueldobbie/markup is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of markup is TypeScript.
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