YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/model-cards#model-card-metadata)

French-TV-transcript-NER is a named-entity recognition model trained specifically on French TV headlines and transcript.

Given the format specificities, generalist multilingual or French model were unperforming. Additionally, the new model also provide additional set of entities useful in production (such as distinction between first name and last name).

Entities

The model covers twelve entities:

  • First name (prenom)
  • Last name (nom)
  • Location (lieu)
  • Country (pays)
  • Organization (organisation)
  • Event (evenement)
  • Nationality (nationalite)
  • Broadcast name (emission)
  • Product (produit), such as technological production, medicine, etc.
  • Law (loi)
  • Cultural creation (creation), such as movie titles, novels, etc.
  • Disease (maladie)
Downloads last month
20
Safetensors
Model size
278M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.