Token Classification
Transformers
GGUF
French
English
mistral
privacy
anonymization
pii
legal
compliance
gdpr
rgpd
ner
on-premise
sovereign-ai
slm
privamesh
Instructions to use sallani/PrivaMesh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sallani/PrivaMesh with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="sallani/PrivaMesh")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("sallani/PrivaMesh") model = AutoModelForTokenClassification.from_pretrained("sallani/PrivaMesh") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 0571881609954c1d7460b66e8c48831cf40609366149443252ea2e383d2f2271
- Size of remote file:
- 187 kB
- SHA256:
- bed4b345965faa63e1a1eec255ee2a06e7d77f30542f0490403516fccee70d91
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