knowledgator/modern-gliner-bi-base-v1.0
Primitive: /extract · Extract ·
GLiNER is a Named Entity Recognition (NER) model capable of identifying any entity type using a bidirectional transformer encoders (BERT-like). It provides a practical alternative to traditional NER models, which are limited to predefined entities, and Large Language Models (LLMs) that, despite t...
Entities
View on Hugging Face → Fine-tuned from answerdotai/ModernBERT-base
Overview
Hardware: — drives latency, throughput & cost
| Size | null params |
|---|---|
| Tasks | /extract |
| License | apache-2.0 |
| Languages | en |
| Latency | 127 ms |
| Throughput | 7.3K tok/s |
| Cost | $0.030 /1M tok |
Cost is approximate — computed from list GPU prices; your actual price depends on the provider you deploy SIE with.
Extraction
| Output kinds | Entities |
|---|---|
| Inputs | text |
| Max sequence length | 2,048 |
Benchmarks
CoNLL-2003
Named entity recognition on Reuters newswire text
Corpus: 3,453 Queries: 3,453
Quality
f1 0.6644
precision 0.6890
recall 0.6415
Performance L4 b1 c16
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