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AI Model Library/Davlan/bert-base-multilingual-cased-ner-hrl
MODEL PROFILE

bert-base-multilingual-cased-ner-hrl

Davlan · bert-base-multilingual-cased-ner-hrl

Hugging Face's logo --- language: - ar - de - en - es - fr - it - lv - nl - pt - zh - 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 not generalize well for all use cases in different domains. The training data for the 10 languages are from:

Text analysislicense:afl-3.0
Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/10/29 08:30:53
OVERVIEW

Model overview

Hugging Face's logo --- language: - ar - de - en - es - fr - it - lv - nl - pt - zh - 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 not generalize well for all use cases in different domains. The training data for the 10 languages are from:

Key features

特点摘要待依据来源补齐，不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

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Frequently asked questions

Do open weights permit free commercial use?

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Sources & traceability

huggingface · Davlan/bert-base-multilingual-cased-ner-hrl ↗2026/10/29 08:30:53
huggingface · enrich:ad568ff6-c095-47eb-8975-26e059ade1f3 ↗2026/10/29 01:35:16

许可证：afl-3.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。