Token Classification
Transformers
PyTorch
Safetensors
English
roberta
deidentification
medical notes
ehr
phi
Instructions to use obi/deid_roberta_i2b2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use obi/deid_roberta_i2b2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="obi/deid_roberta_i2b2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("obi/deid_roberta_i2b2") model = AutoModelForTokenClassification.from_pretrained("obi/deid_roberta_i2b2") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46ff57fe222114ae1f8a4ba96e152963135b2a74c61f31c4bca3018f86e68304
- Size of remote file:
- 1.42 GB
- SHA256:
- 76e5e75ee896f33681a5acf6440d53831a110fd977c71d093260bb94e2a63bfa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.