Instructions to use jammmmmm/pii with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jammmmmm/pii with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jammmmmm/pii")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jammmmmm/pii") model = AutoModelForTokenClassification.from_pretrained("jammmmmm/pii", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from jammmmmm/pii: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/jammmmmm/pii/resolve/main/optimizer.pt
- Command line
-
hf download hf://jammmmmm/pii/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/jammmmmm/pii/resolve/main/optimizer.pt
1.11 GB
- Xet hash:
- 76f5e2c1ac82a3770191a52d25db653eefd5261bd2f3ccdbe5aec59475a1ceb7
- Size of remote file:
- 1.11 GB
- SHA256:
- 549cfaf98d70c5d1b9228fde16d7f5049e4b6a75915460ced13aab0217da656e
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