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-65M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-65M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-65M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-65M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-BloodCancerDetect-TinyMed-65M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
b7ced10 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:903a33336858381538ce1e047daee288e576a1625d889c08606fd16efdca0f0b
size 130398758
|