Rishabh157/krw-spanmarker-multilingual-ner
token-classification model by Rishabh157
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Model card & documentation
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Developed by: Rishabh Kumar Model Name: Rishabh157/krw-spanmarker-multilingual-ner Base Architecture: microsoft/mdeberta-v3-base Framework: SpanMarker An enterprise-grade, state-of-the-art multilingual Named Entity Recognition (NER) model developed by Rishabh Kumar, combining microsoft/mdeberta-v3-base with the SpanMarker candidate span-classification framework. This model is fine-tuned on the master KRW Unified Multilingual NER Dataset (Rishabh157/krw-unified-multilingual-ner), curated by Rishabh Kumar. The dataset harmonizes three foundational benchmarks: WikiANN, MultiCoNER 2023 (v2), and MultiNERD across 15+ languages and fine-grained entity types. Unlike traditional sequence taggers that assign BIO labels token-by-token (which frequently suffer from boundary fragmentation, label inconsistency, and tokenizer-split artifacts), SpanMarker explicitly scores candidate phrase spans directly inside mDeBERTa's disentangled attention mechanism, yielding high boundary accuracy (87.32% Precision and 92.21% Sequence Accuracy). This model was trained on the master unified corpus synthesizing three landmark benchmarks: Evaluated on…
Read the full model card ↗ · Preview checked 2026-10-05T08:34:53.734Z
Inside the original model card — Document outline
- Unified Multilingual SpanMarker NER: mDeBERTa-v3 Fine-Grained (15+ Languages)
- 📚 Training Dataset: KRW Unified Multilingual NER
- Foundational Datasets Integrated:
- Model Details
- Empirical Benchmark Performance
- Qualitative Benchmark & Real-World Evaluation
- Model Labels & Taxonomy
- Category Overview
- Full Label Mapping & Examples
- Usage
- Direct Use for Inference
- Multilingual Batch Inference
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Model overview
Rishabh157/krw-spanmarker-multilingual-ner is a token-classification model repository published by Rishabh157 on Hugging Face. The source reports the span-marker library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- token-classification
- Library
- span-marker
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 277,604,400
- Architecture
- SpanMarkerModel
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-10-05T06:33:41.000Z
- Last modified
- 2026-10-05T06:34:08.000Z
Compatibility and lineage
Reported languages: en, de, es, fr, it, pt, sv, nl, pl, ru, bn, hi, fa, zh, uk, multilingual
Reported base models: microsoft/mdeberta-v3-base
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-05T06:39:49.297Z. Daily imports are snapshots, not real-time monitoring.
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