Token Classification
Transformers
Safetensors
English
eurobert
named-entity-recognition
biomedical-nlp
chemical-entity-recognition
drug-discovery
pharmacology
chemistry
chem
custom_code
Instructions to use EdgeAIMed/EdgeAIMed-NER-ChemicalDetect-EuroMed-212M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EdgeAIMed/EdgeAIMed-NER-ChemicalDetect-EuroMed-212M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="EdgeAIMed/EdgeAIMed-NER-ChemicalDetect-EuroMed-212M", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("EdgeAIMed/EdgeAIMed-NER-ChemicalDetect-EuroMed-212M", trust_remote_code=True) model = AutoModelForTokenClassification.from_pretrained("EdgeAIMed/EdgeAIMed-NER-ChemicalDetect-EuroMed-212M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 197 Bytes
1090347 | 1 2 3 4 5 6 7 | {
"eval_accuracy": 0.9823856835049078,
"eval_f1": 0.9149471967510613,
"eval_loss": 0.32775944471359253,
"eval_precision": 0.9231910946196661,
"eval_recall": 0.9068492282336534
} |