Tinybert Spanish Uncased Finetuned Ner
A named entity recognition model fine-tuned based on Spanish TinyBERT, with a size of only 55MB, suitable for entity recognition tasks in Spanish text.
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Release Time : 3/2/2022
Model Overview
This is a lightweight named entity recognition model trained using knowledge distillation technology, specifically designed to identify various named entities (such as person names, place names, organization names, etc.) in Spanish text.
Model Features
Lightweight and Efficient
The model size is only 55MB, making it more lightweight than traditional BERT models and suitable for resource-constrained environments.
Knowledge Distillation
Trained using knowledge distillation technology, significantly reducing model size while maintaining performance.
Spanish Optimization
A named entity recognition model specifically optimized for Spanish text.
Model Capabilities
Spanish Text Processing
Named Entity Recognition
Entity Classification
Use Cases
Text Analysis
News Entity Extraction
Extract key information such as person names, place names, and organization names from Spanish news.
Can identify 9 types of entity labels such as B-LOC (location) and B-PER (person name).
Social Media Analysis
Analyze mentioned entities in Spanish social media content.
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