# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("BSC-LT/roberta_model_for_anonimization")
model = AutoModelForTokenClassification.from_pretrained("BSC-LT/roberta_model_for_anonimization")Quick Links
This is a Roberta multilingual (Catalan & Spanish) anonimization model, for use with BSC's AnonymizationPipeline at:
https://github.com/TeMU-BSC/AnonymizationPipeline.
The anonymization pipeline is a library for performing sensitive data identification and ultimately anonymization of the detected data in Spanish and Catalan user generated plain text.
This is model can be used as a standalone model but it is meant to work within the pipeline.
The Roberta model can detect the following entities: ORG, PER, LOC
| Type | Score |
|---|---|
ENTS_F |
90.03 |
ENTS_P |
89.7 |
ENTS_R |
90.3 |
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="BSC-LT/roberta_model_for_anonimization")