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README.md

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+pipeline_tag: token-classification
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+Named Entity Recognition (NER) model to recognize chemical entities. 
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+[PubMedBERT](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) fine-tuned on the following datasets:
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+- [Chemdner patents CEMP corpus](https://biocreative.bioinformatics.udel.edu/resources/corpora/chemdner-patents-cemp-corpus/) (train, dev, test sets)
+- [DDI corpus](https://github.com/isegura/DDICorpus) (train, dev, test sets): entity types "GROUP", "DRUG", "DRUG_N"
+- [GREC Corpus](http://www.nactem.ac.uk/GREC/standoff.php) (train, dev, test sets): entity type  "organic_compounds"
+- [MLEE](http://nactem.ac.uk/MLEE/) (train, dev, test sets): entity type "Drug or compound"
+- [NLM-CHEM](https://ftp.ncbi.nlm.nih.gov/pub/lu/NLMChem/) (train, dev, test sets)
+- [CHEMDNER](https://biocreative.bioinformatics.udel.edu/resources/) (train, dev, test sets)
+- [Chebi Corpus](http://www.nactem.ac.uk/chebi/) (train, dev, test sets): entity types "Metabolite", "Chemical"
+- [PHAEDRA](http://www.nactem.ac.uk/PHAEDRA/) (train, dev, test sets): entity type "Pharmalogical_substance"
+- [Chemprot](https://biocreative.bioinformatics.udel.edu/tasks/biocreative-vi/track-5/) (train, dev, test sets)
+- [PGx Corpus](https://github.com/practikpharma/PGxCorpus) (train, dev, test sets): entity type "Chemical"
+- [BioNLP11ID](https://github.com/cambridgeltl/MTL-Bioinformatics-2016/tree/master/data/BioNLP11ID-chem-IOB) (train, dev, test sets): entity type "Chemical"
+- [BioNLP13CG]() (train, dev, test sets): entity type "Chemical"
+- [BC4CHEMD](https://github.com/cambridgeltl/MTL-Bioinformatics-2016/tree/master/data/BC4CHEMD) (train, dev, test sets)
+- [CRAFT corpus](https://github.com/UCDenver-ccp/CRAFT/tree/master/concept-annotation) (train, dev, test sets): entity type "ChEBI"
+- [BC5CDR]() (train, dev, test sets): entity type "Chemical"