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Crysy-rthomas/T-AIA-NER-V2
T-AIA-NER-V2 is a machine learning model from Crysy-rthomas. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
Named Entity Recognition (NER) model trained to identify specific entities in French text. The model is designed to recognize entities such as cities and train stations, which are useful for travel-related applications.
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From the Hugging Face model README
Named Entity Recognition (NER) model trained to identify specific entities in French text. The model is designed to recognize entities such as cities and train stations, which are useful for travel-related applications.
The model is based on the AutoModelForTokenClassification architecture from the Hugging Face Transformers library. It uses a pre-trained transformer model fine-tuned on a custom dataset for NER tasks.
The model was trained on a dataset of French train stations and cities. The data was preprocessed and converted into a format suitable for NER tasks. The training data includes various sentences with labeled entities.
The model recognizes the following labels:
O: Outside of a named entityB-START: Beginning of a start entityI-START: Inside of a start entityB-END: Beginning of an end entityI-END: Inside of an end entityYou can use this model with the Hugging Face transformers library.