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@@ -10,13 +10,15 @@ pipeline_tag: token-classification
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  [![GitHub](https://img.shields.io/badge/GitHub-omicsNLP%2FmicrobELP-blue?logo=github)](https://github.com/omicsNLP/microbELP)
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  [![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://github.com/omicsNLP/microbELP/blob/main/LICENSE)
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- # 🦠 MicrobELP — Microbiome Entity Recognition
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- MicrobELP is a deep learning model for Microbiome Entity Recognition, identifying microbial entities (bacteria, archaea, fungi) in biomedical and scientific text.
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  It is part of the [microbELP](https://github.com/omicsNLP/microbELP) toolkit and has been optimised for CPU and GPU inference.
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  This model enables automated extraction of microbiome names from unstructured text, facilitating microbiome-related text mining and literature curation.
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  ## 🚀 Quick Start (Hugging Face)
 
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  [![GitHub](https://img.shields.io/badge/GitHub-omicsNLP%2FmicrobELP-blue?logo=github)](https://github.com/omicsNLP/microbELP)
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  [![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://github.com/omicsNLP/microbELP/blob/main/LICENSE)
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+ # 🦠 MicrobELP — Microbiome Entity Recognition and Normalisation
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+ MicrobELP is a deep learning model for Microbiome Entity Recognition and Normalisation, identifying microbial entities (bacteria, archaea, fungi) in biomedical and scientific text.
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  It is part of the [microbELP](https://github.com/omicsNLP/microbELP) toolkit and has been optimised for CPU and GPU inference.
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  This model enables automated extraction of microbiome names from unstructured text, facilitating microbiome-related text mining and literature curation.
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+ We also provide an Named Entity Normalisation model on Hugging Face: [![Hugging Face Models](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-microbELP_NEN-FFD21E)](https://huggingface.co/omicsNLP/microbELP_NEN)
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  ---
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  ## 🚀 Quick Start (Hugging Face)