
Named Entity Recognition (NER) model to recognize cell component entities.
[PubMedBERT](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) fine-tuned on the following datasets:
- [CRAFT](https://github.com/UCDenver-ccp/CRAFT/tree/master/concept-annotation): entity type "GO-CC"
- [MLEE](http://nactem.ac.uk/MLEE/): entity type "Cellular_component"
- [BioNLP13CG-cc](https://github.com/cambridgeltl/MTL-Bioinformatics-2016/tree/master/data/BioNLP13CG-cc-IOB)
{"language": ["en"], "pipeline_tag": "token-classification"}
transformers pytorch bert token-classification en autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #token-classification #en #autotrain_compatible #endpoints_compatible #region-us 


Named Entity Recognition (NER) model to recognize cell component entities.
PubMedBERT fine-tuned on the following datasets:
- CRAFT: entity type "GO-CC"
- MLEE: entity type "Cellular_component"
- BioNLP13CG-cc
TAGS
#transformers #pytorch #bert #token-classification #en #autotrain_compatible #endpoints_compatible #region-us 

TAGS
#transformers #pytorch #bert #token-classification #en #autotrain_compatible #endpoints_compatible #region-us 
