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
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README.md
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```bibtex
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@misc{privamesh2026legal,
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title = {PrivaMesh: A Collaborative Multi-SLM Framework for Semantic Data Anonymization in Sovereign Agentic AI Pipelines},
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author = {
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year = {2026},
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publisher = {HuggingFace},
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url = {https://huggingface.co/sallani/PrivaMesh},
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```bibtex
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@misc{privamesh2026legal,
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title = {PrivaMesh: A Collaborative Multi-SLM Framework for Semantic Data Anonymization in Sovereign Agentic AI Pipelines},
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author = {Sabri ALLANI et Ahmed HERSI},
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year = {2026},
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publisher = {HuggingFace},
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url = {https://huggingface.co/sallani/PrivaMesh},
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