About the Model An English Named Entity Recognition model, trained on Maccrobat to recognize the bio medical entities (107 entities) from a given text corpus (case reports etc.). This model was built on top of distilbert base uncased Dataset: Maccrobat https://figshare.com/articles/dataset/MACCROBAT2018/9764942 Carbon emission: 0.0279399890043426 Kg Training time: 30.16527 minutes GPU used : 1 x GeForce RTX 3060 Laptop GPU Checkout the tutorial video for explanation of this model and corresponding python library: https://youtu.be/xpiDPdBpS18 Usage The easiest way is to load the inference api from huggingface and second method is through the pipeline object offered by transformers library. Author This model is part of the Research topic "AI in Biomedical field" conducted by Deepak John Reji, Shaina Raza. If you use this work (code, model or dataset), please star at: https://github.com/dreji18/Bio Epidemiology NER You can support me here :)
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