Token Classification
Transformers
Safetensors
English
distilbert
named-entity-recognition
biomedical-nlp
species-recognition
taxonomy
organism-identification
biodiversity
species
Instructions to use OpenMed/OpenMed-NER-OrganismDetect-TinyMed-135M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-OrganismDetect-TinyMed-135M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-OrganismDetect-TinyMed-135M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-OrganismDetect-TinyMed-135M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-OrganismDetect-TinyMed-135M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba3e5a56463aa63999219d6ac4633ee8427b494943f999dcd7db65fe775d9d5c
- Size of remote file:
- 269 MB
- SHA256:
- 4b51887f1ad8cbdca332f27414b8c12c98993ecb3679f9267e59b23991bb0a3f
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