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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
1 line for thousands of State of The Art NLP models in hundreds of languages The fastest and most accurate way to solve text problems.
| Date | Stars |
|---|---|
| 2026-07-24 | 968 |
| 2026-07-25 | 968 |
| 2026-07-28 | 968 |
| 2026-07-30 | 968 |
| 2026-08-06 | 968 |
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# NLU: The Power of Spark NLP, the Simplicity of Python John Snow Labs' NLU is a Python library for applying state-of-the-art text mining, directly on any dataframe, with a single line of code. As a facade of the award-winning Spark NLP library, it comes with **1000+** of pretrained models in **100+**, all production-grade, scalable, and trainable, with **everything in 1 line of code.** ## NLU in Action See how easy it is to use any of the **thousands** of models in 1 line of code, there are hundreds of [tutorials](https://nlu.johnsnowlabs.com/docs/en/notebooks) and [simple examples](https://github.com/JohnSnowLabs/nlu/tree/master/examples) you can copy and paste into your projects to achieve State Of The Art easily. <img src="http://ckl-it.de/wp-content/uploads/2020/08/My-Video6.gif" width="1800" height="500"/> ## NLU & Streamlit in Action This 1 line let's you visualize and play with **1000+ SOTA NLU & NLP models** in **200** languages ```shell streamlit run https://raw.githubusercontent.com/JohnSnowLabs/nlu/master/examples/streamlit/01_dashboard.py ``` <img src="https://raw.githubusercontent.com/JohnSnowLabs/nlu/master/docs/assets/streamlit_docs_assets/gif/start.gif"> NLU provides tight and simple integration into Streamlit, which enables building powerful webapps in just 1 line of code which showcase the. View the [NLU&Streamlit documentation](https://nlu.johnsnowlabs.com/docs/en/streamlit_viz_examples) or [NLU & Streamlit examples section](https://github.com/JohnSnowLabs/nlu/tree/master/examples/streamlit). The entire GIF demo and ## All NLU resources overview Take a look at our official NLU page: [https://nlu.johnsnowlabs.com/](https://nlu.johnsnowlabs.com/) for user documentation and examples | Ressource | Description| |-----------------------------------------------------------------------|-------------------------------------------| | [Install NLU](https://nlu.johnsnowlabs.com/docs/en/install) | Just run `pip install nlu pyspark==3.0.2` | [The NLU Namespace](https://nlu.johnsnowlabs.com/docs/en/namespace) | Find all the names of models you can load with `nlu.load()` | [The `nlu.load(<Model>)` function](https://nlu.johnsnowlabs.com/docs/en/load_api) | Load any of the **1000+ models in 1 line** | [The `nlu.load(<Model>).predict(data)` function](https://nlu.johnsnowlabs.com/docs/en/predict_api) | Predict on `Strings`, `List of Strings`, `Numpy Arrays`, `Pandas`, `Modin` and `Spark Dataframes` | [The `nlu.load(<train.Model>).fit(data)` function](https://nlu.johnsnowlabs.com/docs/en/training) | Train a text classifier for `2-Class`, `N-Classes` `Multi-N-Classes`, `Named-Entitiy-Recognition` or `Parts of Speech Tagging` | [The `nlu.load(<Model>).viz(data)` function](https://nlu.johnsnowlabs.com/docs/en/viz_examples) | Visualize the results of `Word Embedding Similarity Matrix`, `Named Entity Recognizers`, `Dependency Trees & Parts of Speech`, `Entity Resolution`,`Entity Linking` or `Entity Status Assertion` | [The `nlu.load(<Model>).viz_streamlit(data)` function](https://nlu.johnsnowlabs.com/docs/en/streamlit_viz_examples) | Display an interactive GUI which lets you explore and test every model and feature in NLU in 1 click. | [General Concepts](https://nlu.johnsnowlabs.com/docs/en/concepts) | General concepts in NLU | [The latest release notes](https://nlu.johnsnowlabs.com/docs/en/release_notes) | Newest features added to NLU | [Overview NLU 1-liners examples](https://nlu.johnsnowlabs.com/docs/en/examples)
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Juan Martinez · FRVR.ai · Portugal
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WeichenXu · @databricks
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Maziyar Panahi · @ISCPIF · United Kingdom
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Luca Martial · Kaelio · United States
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:6009858531c2f150, topic:named-entity-recognition, topic:text-classification, topic:sentiment-analysis