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- entity recognition
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- NER
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- named entity recognition
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- zero-shot
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---
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NuZero - is the family of Zero-Shot Entity Recognition models inspired by [GLiNER](https://huggingface.co/papers/2311.08526)
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NuZero span is a more powerful version of GLiNER-large-v2.1, surpassing it by 4% on average, and is trained on the diverse internal dataset tailored for real-life use cases.
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<p align="center">
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<img src="zero_shot_performance_span.png">
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</p>
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- entity recognition
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- NER
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- named entity recognition
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- zero shot
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- zero-shot
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---
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NuZero - is the family of Zero-Shot Entity Recognition models inspired by [GLiNER](https://huggingface.co/papers/2311.08526) and built with insights we gathered throughout our work on [NuNER](https://arxiv.org/abs/2402.15343).
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NuZero span is a more powerful version of GLiNER-large-v2.1, surpassing it by 4% on average, and is trained on the diverse internal dataset tailored for real-life use cases.
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<p align="center">
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<img src="zero_shot_performance_span.png">
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</p>
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## Installation & Usage
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```
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!pip install gliner
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```
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```python
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from gliner import GLiNER
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model = GLiNER.from_pretrained("numind/NuZero_span")
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text = """
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"""
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labels = ["person", "award", "date", "competitions", "teams"]
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entities = model.predict_entities(text, labels)
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for entity in entities:
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print(entity["text"], "=>", entity["label"])
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```
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## Fine-tuning
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