Token Classification
Transformers
Safetensors
English
distilbert
named-entity-recognition
biomedical-nlp
leukemia
hematology
cancer
clinical-medicine
cl
Instructions to use OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-135M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-135M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-135M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-135M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-135M", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
feat: Upload fine-tuned medical NER model OpenMed-NER-BloodCancerDetect-TinyMed-135M
7642248 verified | { | |
| "eval_accuracy": 0.9667832167832168, | |
| "eval_f1": 0.8792270531400966, | |
| "eval_loss": 0.3497123122215271, | |
| "eval_precision": 0.875, | |
| "eval_recall": 0.883495145631068 | |
| } |