David Adelani

Model · Token classification

xlm-roberta-base-ner-hrl

David Adelani

Hugging Face's logo - multilingual xlm-roberta-base-ner-hrl is a Named Entity Recognition model for 10 high resourced languages (Arabic, German, English, Spanish, French, Italian, Latvian, Dutch, Portuguese and Chinese) based on a fine-tuned XLM-RoBERTa base model. It has been trained to recognize three types of entities: location (LOC), organizations (ORG), and person (PER). Specifically, this model is a xlm-roberta-base model that was fine-tuned on an aggregation of 10 high-resourced languages You can use this model with Transformers pipeline for NER. This model is limited by its training dataset of entity-annotated news articles from a specific span of time. This may not generalize well…

Model · Token classification

bert-base-multilingual-cased-ner-hrl

David Adelani

Hugging Face's logo - multilingual bert-base-multilingual-cased-ner-hrl is a Named Entity Recognition model for 10 high resourced languages (Arabic, German, English, Spanish, French, Italian, Latvian, Dutch, Portuguese and Chinese) based on a fine-tuned mBERT base model. It has been trained to recognize three types of entities: location (LOC), organizations (ORG), and person (PER). Specifically, this model is a bert-base-multilingual-cased model that was fine-tuned on an aggregation of 10 high-resourced languages You can use this model with Transformers pipeline for NER. This model is limited by its training dataset of entity-annotated news articles from a specific span of time. This may…