Model overview
**Model Name:** MEL (Modelo de Español Legal) **Model Type:** Encoder-only Transformer **Language:** Spanish **Domain:** Legal Texts **Paper:** Link to paper MEL is a transformer-based language model designed specifically for processing and understanding Spanish legal texts. Built upon **XLM-RoBERTa-large**, it is further pre-trained on a **large corpus of legal documents**, including the **Boletín Oficial del Estado (BOE), parliamentary transcripts, court rulings, and other legislative texts**. MEL significantly improves the performance of legal NLP tasks, such as **legal text classification** and **named entity recognition (NER)**. MEL is trained on a **curated corpus** of **5.52 million legal texts (~92.7GB)** sourced from: - **BOE (Boletín Oficial del Estado)** - **Parliamentary records** - **Court rulings** - **Legal statutes**
Key features
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Limitations & considerations
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Public benchmarks & run configuration
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Sources & traceability
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