Instructions to use SaffalPoosh/t5_confidential_masking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SaffalPoosh/t5_confidential_masking with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("SaffalPoosh/t5_confidential_masking") model = AutoModelForSeq2SeqLM.from_pretrained("SaffalPoosh/t5_confidential_masking", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e422ebd0a3d7c1384ab86b7dc9abba12ef154398677eefb378c7228956f46d94
- Size of remote file:
- 5.37 kB
- SHA256:
- 4ceb12e70511de98b2cc9ce7f06c5d585d52e7f7f190f0ad6b77577467a2dfdc
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