Text Classification
Transformers
PyTorch
English
deberta-v2
Trained with AutoTrain
healthcare
sdoh
social determinants of health
text-embeddings-inference
Instructions to use ClinicalNLP/SDOHv7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ClinicalNLP/SDOHv7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ClinicalNLP/SDOHv7")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ClinicalNLP/SDOHv7") model = AutoModelForSequenceClassification.from_pretrained("ClinicalNLP/SDOHv7") - Notebooks
- Google Colab
- Kaggle
Added code to map outputs back to the labels
#4
by nadaaaita - opened
I added code to extract the probabilities and map them back to the class labels. I was a bit confused about how to do it and it took me a minute to figure it out. So I thought this might be helpful to others.
I added code to extract the probabilities and map them back to the class labels. I was a bit confused about how to do it and it took me a minute to figure it out. So I thought this might be helpful to others.
Thank you !!!