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:
- e88c2eb619b1f82879786c278d1701c9dab34c0289d41c062f1ed49885b459b5
- Size of remote file:
- 175 kB
- SHA256:
- 84654e6fc8b9907ae3bfbc85e4ed8b69ba89c45dee55577b3218e318bc777b7c
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