Token Classification
Transformers
Safetensors
German
English
modernbert
gdpr
dsgvo
privacy
pii
ner
anonymization
pseudonymization
Instructions to use allsmart/Art4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allsmart/Art4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="allsmart/Art4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("allsmart/Art4") model = AutoModelForTokenClassification.from_pretrained("allsmart/Art4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from allsmart/Art4: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/allsmart/Art4/resolve/main/tokenizer.json
- Command line
-
hf download hf://allsmart/Art4/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/allsmart/Art4/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- 4979ea4051b704efcb2a1a34961c5f93d2fa004f33c607d894c7ebe32511f588
- Size of remote file:
- 34.4 MB
- SHA256:
- f34b44a6dc8a0eef651bfa10e8325057530152606a69d9c3b6ae02efb1558f0a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.