Updated docs

Author: Pringled

README.md

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-SemHash is a lightweight library for semantic deduplication, outlier filtering, and representative sample selection. It's fully multimodal: text works out-of-the-box with fast [Model2Vec](https://github.com/MinishLab/model2vec) embeddings, and you can bring your own encoders for images, audio, or custom models.
+SemHash is a lightweight, multimodal library for semantic deduplication, outlier filtering, and representative sample selection. Text works out of the box with fast [Model2Vec](https://github.com/MinishLab/model2vec) embeddings, and images, audio, and other modalities are supported with custom encoders.
 
 SemHash supports both single-dataset operations (clean a training set) and cross-dataset operations (deduplicate test against train). It works with simple lists and complex multi-column datasets, and includes inspection tools to help you understand and refine results. All operations use [Vicinity](https://github.com/MinishLab/vicinity) for efficient similarity search.