GLiNER2.5 Multi V1
GLiNER2.5 Multi is a 0.3B parameter multilingual span free information extraction model that predicts entity boundaries directly instead of enumerating candidate spans. It performs named entity recognition, relation extraction, and constrained classification across languages, scoring an average F1 of 56.17 across 16 benchmarks, with demonstrated cross lingual generalization.
- Type
- Text
- Weights
- Open
- Downloads
- 252k
- Likes
- 260
- Pipeline
- token classification
- License
- apache-2.0
Model hub
fastino/gliner2.5-multi-v1
- Repo
- fastino/gliner2.5-multi-v1
- Library
- gliner2
- Access
- Public
Technical tags and languages
Papers
1
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About Fastino
1
Task-optimized language models (TLMs) that are more accurate, faster, and safer than traditional LLMs, running without GPUs