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 training_args.bin from KindLab/roberta-deid: direct link, hf CLI and curl.
- Browser
- Download file 3.25 kB
-
https://huggingface.co/KindLab/roberta-deid/resolve/main/training_args.bin
- Command line
-
hf download hf://KindLab/roberta-deid/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/KindLab/roberta-deid/resolve/main/training_args.bin
3.25 kB
- Xet hash:
- 3d1e77d0b7818e65b7815dfa265b4ca0ff428143ee4777a96e4d7a6af0edc968
- Size of remote file:
- 3.25 kB
- SHA256:
- 9ed2bd59fe0d0ec5fc11a6f898224d39d7c74fa23fd9791a6a188c65cd74fbae
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