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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("obi/deid_roberta_i2b2") model = AutoModelForTokenClassification.from_pretrained("obi/deid_roberta_i2b2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from obi/deid_roberta_i2b2: direct link, hf CLI and curl.
- Browser
- Download file 239 Bytes
-
https://huggingface.co/obi/deid_roberta_i2b2/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://obi/deid_roberta_i2b2/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/obi/deid_roberta_i2b2/resolve/main/special_tokens_map.json
239 Bytes
| {"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": false}} |