Token Classification
Transformers
Safetensors
English
roberta
named-entity-recognition
biomedical-nlp
leukemia
hematology
cancer
clinical-medicine
cl
Instructions to use OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-82M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-82M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-82M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-82M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-82M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
feat: Upload fine-tuned medical NER model OpenMed-NER-BloodCancerDetect-TinyMed-82M
76142fb verified | { | |
| "eval_accuracy": 0.9449300699300699, | |
| "eval_f1": 0.8793456032719837, | |
| "eval_loss": 0.42400670051574707, | |
| "eval_precision": 0.7904411764705882, | |
| "eval_recall": 0.9907834101382489 | |
| } |