Instructions to use KindLab/roberta-deid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KindLab/roberta-deid with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="KindLab/roberta-deid")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("KindLab/roberta-deid") model = AutoModelForTokenClassification.from_pretrained("KindLab/roberta-deid", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from KindLab/roberta-deid: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/KindLab/roberta-deid/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://KindLab/roberta-deid/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/KindLab/roberta-deid/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- e51a2856a93e7f32a90f7889855fab852af2a172be047a18e5663bd84e5742a4
- Size of remote file:
- 496 MB
- SHA256:
- 52c34b21034ad1933e3ed08d18e44707133e8cb93fe82ec9efa39dd0441ef894
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